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10 New Cloud Security Trends for Better Technology Management

10 New Cloud Security Trends for Better Technology Management
Enhance security by leveraging the latest cloud security trends, including identity and access management, data encryption, cloud-native security, threat intelligence, and policy development.


Table of Contents

Why Should Organizations Leverage Cloud Security Management Now?
Top Trends in Cloud Security and Cloud-native Security Navigating Cloud Security Future Trends

In an AI-dominated and digitally connected world where the stakes of cloud security have reached unprecedented heights, protecting the valuable cloud assets of cloud companies has become indispensable. With the attack surface expanding alarmingly, merely relying on traditional security measures is no longer enough.

As organizations grapple with securing access, storage, data in transit, data at rest, and compliance, the demand for cutting-edge cloud security solutions is skyrocketing. Staying ahead of the curve by embracing the latest cloud security trends is a priority to safeguard digital infrastructure and outpace the top trends in cloud security threats.

According to Fortune Business Insights, the global cloud security market size was valued at USD 29.26 billion in 2021 and is projected to grow from USD 33.13 billion in 2022 to USD 106.02 billion by 2029, exhibiting a CAGR of 18.1% during 2022–2029.

Why Should Organizations Leverage Cloud Security Management Now?

Embracing cloud security management empowers organizations to scale efficiently, reduce operational complexities, and enhance overall resilience, safeguarding critical data and services in the face of modern-day security challenges.
 
Cloud security management tools offer numerous benefits, including:
 
  • Enhanced Security: Cloud security tools offer advanced encryption, authentication, access control, and data loss prevention. They identify and mitigate vulnerabilities, enforce security policies, and detect and respond to incidents promptly.
  • Centralized Management: These tools provide a unified platform to manage security across multiple cloud services. They simplify security management, improve efficiency, and enforce consistent policies.
  • Automated Compliance: Some of the tools automate compliance with regulatory standards by providing pre-configured controls, monitoring, and logging capabilities.
  • Threat Intelligence and Monitoring: These tools use machine learning and analytics to detect and analyze security events, providing proactive alerts and facilitating incident response.
  • Scalability and Flexibility: Cloud security tools scale with cloud environments, support multi-cloud and hybrid setups, and integrate with existing security solutions.
  • Cost Efficiency: Automate cloud security tasks to reduce manual efforts, optimize resource allocation, and minimize operational costs.
  • Continuous Improvement: Cloud security tools offer updates, patches, and feature enhancements to address emerging threats and improve security practices.


Top Cloud Security Trends for Secure Management

Leverage these exclusive insights into the top trends in cloud security and cloud-native security, equipping organizations with essential information to efficiently fortify digital assets as the attack surface expands.
 

1.    Least Privilege and Temporary Credentials in IAM

Implementing the principle of least privilege has turned out to be one of the top cloud security trends that is essential for minimizing the attack surface and reducing the risk of unauthorized access. By granting users only the permissions they need for a specific period, organizations can enhance their overall security posture. Additionally, employing just-in-time access provisioning and time-limited credentials further fortifies the system against potential threats. Organizations can implement least privilege by using role-based access control (RBAC) and attribute-based access control (ABAC) to define granular permissions. Temporary credentials can be issued through mechanisms such as single sign-on (SSO) and multi-factor authentication (MFA) to enhance security.
 

2.    Encrypt Both Data in Transit and Data at Rest

Advanced encryption techniques are crucial to protecting sensitive information in cloud environments. Encrypting data both during transmission and storage is one of the trends in cloud security that ensures that even if intercepted, unauthorized access is prevented. By utilizing robust encryption algorithms and implementing proper key management practices, organizations can safeguard their data throughout its lifecycle, mitigating the risk of data breaches. Organizations can use encryption protocols such as Transport Layer Security (TLS) and Secure Sockets Layer (SSL) to secure data in transit. For data at rest, encryption methods such as Advanced Encryption Standard (AES) and RSA can be used. Key management is also crucial, and organizations can use hardware security modules (HSMs) or cloud-based key management services to securely store and manage encryption keys.
 

3.    Managed Cloud Services for Implementing Zero Trust

Cloud service providers offer managed services that facilitate the implementation of zero-trust architectures. By partnering with these providers, organizations can integrate zero-trust principles into their infrastructure, applications, and network design. This is quickly becoming the industry norm among the various new trends in cloud security. Robust identity and access management solutions, network segmentation, and continuous authentication contribute to establishing a comprehensive zero-trust framework, enhancing overall security resilience. Managed cloud services such as Amazon Web Services (AWS) Security Hub, Microsoft Azure Security Center, and Google Cloud Security Command Center provide tools and features to help organizations implement zero trust. These services offer features such as identity and access management, network segmentation, and continuous monitoring to help organizations establish a zero-trust architecture.
 

4.    Securing Cloud-native Environments and Serverless Architectures

Securing cloud-native environments and serverless architectures requires specialized security measures, including a DevSecOps approach. Organizations should adopt security tools and practices tailored specifically for cloud-native applications, microservices, containers, and serverless functions. This includes implementing runtime protection, vulnerability scanning, and container image scanning to effectively mitigate emerging threats. One of the latest cloud security trends is to utilize tools such as Kubernetes-native security solutions, container image scanning tools, and serverless security platforms to secure their cloud-native environments. Additionally, implementing a DevSecOps approach that integrates security into the development process can help organizations proactively address security concerns.
 

5.    Introducing AI and ML-based Cloud Threat Intelligence

Leveraging the power of artificial intelligence and machine learning for cloud threat intelligence is becoming increasingly important. By utilizing machine learning algorithms to analyze vast amounts of data, organizations can identify patterns, anomalies, and potential security risks in real-time. AI-powered threat detection and incident response systems enable early threat detection, streamline security operations, and improve incident response times. AI and ML-based cloud threat intelligence solutions can help organizations detect threats in real-time by analyzing large amounts of data from various sources. These solutions can identify patterns and anomalies that may indicate potential security risks, enabling organizations to take proactive measures to mitigate threats.
 

6.    Building Heterogeneous Cloud Security Policy

Organizations operating in multi-cloud or hybrid cloud environments face the challenge of managing security across different cloud platforms. Building a unified and adaptable cloud security policy is crucial for the consistent application of security controls. This comprehensive policy framework should address the specific security requirements and nuances of various cloud providers and deployment models, ensuring a robust security posture. Organizations must use policy management tools to create a unified cloud security policy that addresses the specific requirements of different cloud platforms. This policy should be adaptable to changes in the cloud environment and should be regularly reviewed and updated to ensure its effectiveness.
 

7.    Cloud Security Automation and Continuous Patching of Vulnerabilities

Automation plays a critical role in cloud security management. By automating security processes and leveraging continuous patching, organizations can streamline their security operations, reduce human error, and promptly address vulnerabilities. Automated patch management ensures that systems are up-to-date, minimizing the risk of exploitation due to known vulnerabilities. Organizations can use automation tools such as configuration management systems, patch management solutions, and vulnerability scanners to automate their cloud security processes. Continuous patching ensures that systems are always up-to-date with the latest security patches, reducing the risk of exploitation due to known vulnerabilities.
 

8.    Cloud Security Posture Management

Cloud Security Posture Management (CSPM) is one of the security trends in cloud computing that continuously monitors and manages cloud infrastructure security. It assesses resources, configurations, and policies for compliance with best practices and regulations. CSPM provides visibility, identifies misconfigurations and vulnerabilities, and offers remediation recommendations. CSPM includes cloud configuration monitoring, vulnerability assessment, compliance monitoring, threat detection, remediation, automation, and continuous monitoring to ensure compliance, detect threats, and maintain a strong security posture. CSPM solutions provide organizations with visibility into their cloud infrastructure security posture by continuously monitoring resources, configurations, and policies for compliance with best practices and regulations. These solutions can identify misconfigurations and vulnerabilities, provide remediation recommendations, and automate the remediation process to improve overall security resilience.
 

9.    Prioritization of Cloud Security Alerts

As cloud environments generate numerous security alerts, it is crucial to prioritize them effectively. Utilizing intelligent alert prioritization mechanisms. It is one of the evolving cloud security management trends where organizations can focus their resources on addressing the most critical threats. This approach improves incident response efficiency and reduces response time, ultimately strengthening the overall security posture. Organizations can use tools such as Security Information and Event Management (SIEM) systems, Security Orchestration, Automation, and Response (SOAR) platforms, and AI/ML-based solutions to prioritize cloud security alerts. These tools can analyze alerts in real-time, correlate them with other security data, and assign a priority level based on the potential impact of the threat.
 

10.  Public Cloud Data Security Trends

Securing public cloud data is one of the top cloud security trends and a growing concern. Organizations must reinforce security measures to address the challenges posed by shadow, orphan, and democratized data. By implementing robust data protection strategies, including access controls, encryption, and data loss prevention mechanisms, organizations can safeguard their data from unauthorized access and potential breaches. Organizations can enforce measures such as data classification, data access controls, and data encryption to secure their public cloud data. Additionally, implementing data loss prevention (DLP) mechanisms can help prevent data breaches by detecting and blocking unauthorized data transfers. Regularly monitoring and auditing data access and usage can also help organizations identify and address potential security risks. Cloud data security trends equip companies with robust security measures to tackle data-related threats and vulnerabilities effectively.
 

Navigating Cloud Security Future Trends

Keeping on top of the latest cloud security management trends is essential for organizations to secure data and valuable assets and maintain an optimally secure cloud infrastructure. From adopting zero-trust architecture to implementing container security and embracing DevSecOps, there are numerous options to enhance security posture in the dynamic cloud landscape. Cloud-native security, data encryption, and automated incident response are also reshaping cloud security future trends and practices. Leveraging AI and machine learning technologies becomes imperative to bolster threat intelligence and monitoring capabilities as threats evolve.
 
By proactively implementing robust cloud security management practices aligned with these emerging trends, organizations can effectively safeguard data, mitigate risks, and maintain trust with customers and stakeholders. It is crucial to recognize that cloud security is an ongoing process that requires continuous adaptation to the evolving threat landscape. Organizations can integrate emerging trends into their cloud security strategies to navigate the complexities of the cloud confidently, ensuring the protection of critical assets and fostering a resilient digital infrastructure. Stay ahead of the curve and secure cloud environments for a successful and protected digital journey.

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Leading Data Warehouse Software Vendors That Enhance Analytics

Article | July 27, 2023

From amplified scalability to data transparency, top data warehouse software vendors boost businesses’ analysis capabilities. Learn how companies gain data agility with cloud data warehouse software. Contents 1. Understanding the Fundamentals of a Cloud Data Warehouse 2. Key Advantages of Data Warehousing for Businesses 3. Data Warehouse Strategies to Integrate and Analyze Data 4. Top Data Warehouse Software Vendors Offering Analytics Prowess 4.1 Dremio 4.2 Starburst 4.3 Firebolt 4.4 Lyftrondata 4.5 CData 4.6 Zap 4.7 Druid 4.8 TimeXtender 4.9 dbt Labs 4.10 Redwood Software 5. Final Thoughts 1. Understanding the Fundamentals of a Cloud Data Warehouse Representing a robust solution for handling and storing vast datasets, a cloud data warehouse offers businesses high convenience, quick data access, and remarkable flexibility. The data warehouse is essentially hosted in a cloud computing environment that empowers organizations to modify storage and processing as and when required without needing hardware upgrades. The growing prominence of the advanced setup today can notably be ascribed to its unparalleled accessibility, which allows companies to manage their data from any part of the world via internet access. Likewise, the warehouse’s core components include a centralized repository with distinct computing abilities, which enable scalable data retention and optimized resource allocation. Moreover, the data warehouse software boasts phenomenal data integration and handling tools, allowing businesses to link to diverse data sources, build datasets, set permissions, and run queries. It further boosts companies’ performances through parallel query processing, system backups, data encryption, etc. Moreover, supporting innovative analytics and insights, the cloud environment enables businesses to make data-backed decisions, augmenting their analytics prowess and driving high ROIs. 2. Key Advantages of Data Warehousing for Businesses From enhanced financial efficiencies to unmatched data access, data warehousing practices offer multiple benefits to businesses that allow sound decision-making and operational success. The chief merits of a data warehouse software include: Scalable Infrastructure for Unhindered Productivity With a cloud data warehouse, businesses can effortlessly adjust resources to handle diverse data processing requirements and scale up or down without bearing upgrade costs ascribed to traditional on-premises systems. By simply modifying payment schemes, companies can increase or decrease their computing power or storage, paying only for what they use. The unparalleled scalability further enables businesses to ensure undisturbed operations, faster innovations, and speed-to-market, benefiting from high agility in operations and augmenting business productivity. Quick Data Access Cloud data warehouses enhance data availability exponentially. They unify diverse data into a centralized repository, enabling users to access data quickly from anywhere in the world via web access. This flexible access, in turn, encourages remote work and collaboration endeavors, promoting real-time decision-making and augmenting operational responsiveness. Enhanced Visual Data Analysis With leading-edge business intelligence tools, advanced data warehouses support swift data processing, empowering businesses to extract crucial insights and analyze data in real time. The boosted analytics and data visualization abilities help companies make sound decisions and stay ahead of the curve. Cost-effectiveness A cloud data warehouse is a more economical substitute for on-premises systems. It works on a pay-as-you-go model, eliminating the need for physical hardware. Therefore, companies pay only for the computing resources and storage they use. Most data warehouse providers offer flexible pricing models, enabling businesses to maintain cost-efficient systems for data warehousing. Robust Security and Disaster Recovery A significant advantage of the cloud data warehouse is that it implements notable security measures like access controls, data encryption, and periodic security audits to protect sensitive business data and information from unauthorized breaches. It offers all-inclusive disaster recovery solutions, including scheduled backups and data replication across various geographic locations. Such features secure unhindered functions and data resilience in times of unanticipated interruptions. Performance Excellence Boasting features like distributed computing and parallel processing, cloud data warehouses guarantee elevated business performance as they quicken data analysis and query execution. From optimizing operations through automated tasks to eliminating the need for costly hardware investments, data warehouse setups on the cloud promise boosted productivity and efficiency. Impressive Integrations Cloud data platforms offer impressive integration capabilities, helping businesses connect with various data origins and third-party applications. Such incorporations expedite effective data reporting and analysis and augment businesses’ ability to extract valuable insights, showcasing the advantage of data warehouse integration and leading to better performance. Reliable Support and Ease-of-Use Established cloud data warehouse providers render round-the-clock support to businesses, ensuring uninterrupted operations and prompt problem resolutions. The warehouse, which comprises intuitive user interfaces, simplifies data access for non-technical teams, reducing dependency on IT staff and enabling the autonomous performance of data tasks, such as data reading, editing, and writing, through low-code or codeless platforms. 3. Data Warehouse Strategies to Integrate and Analyze Data Businesses employ various data warehousing techniques and strategies, like ETL or incremental loading, to maintain excellent quality in business processes and secure optimized performance. Here’s a breakdown of the prominent data warehouse strategies that companies leverage to derive crucial insights and gain remarkable scalability: Effective Metadata Categorization With strong metadata categorization, businesses can enhance data extraction and organization, simplifying data queries and augmenting accessibility. The centralized metadata management further documents data usage, lineage, and definitions, facilitating efficient data governance. The strategy helps stakeholders easily find and understand the required data, ensures compliance with data use regulations, and promotes data transparency and availability within the company. ETL Technique for Data Integration Through the ETL processes, i.e., extract, transform, load, data can be retrieved from diverse sources, transformed to match the warehouse schema, and loaded into the target system or data warehouse. This strategy is pivotal for incorporating data into the setup. It effectively streamlines data flows and allows businesses to conduct impactful data analysis. Data Segmentation and Indexing Also called ‘partitioning’, data segmentation involves dividing vast tables into easy-to-manage segments, maximizing data extraction, storage, and management. Each of these segments or ‘partitions’, therefore, holds a subset of the large table’s data, divided according to established criteria, like hash keys or value ranges. Indexing, likewise, allows speedy data retrieval based on specific criteria, as it creates systematized lists of the table’s fundamental values. Collectively, these promising strategies optimize query processing and database management, ensuring responsiveness with increasing data volumes. Data Modeling Strategy Data can be organized effectively for optimum querying by leveraging techniques like star or snowflake schemas. For instance, measurable data like sales can be stored in fact tables, while attributes like time or location are stored in dimension tables. Hence, the data modeling strategy makes it simpler to ask intricate questions about data, boosting performance and enabling easy-to-understand data analysis and exploration. Incremental Loading for Quicker Data Processing Another prominent data warehousing strategy is incremental loading. This strategy involves speeding up information handling processes by only making changes since the last data update. While the previous data remains unchanged, only new data gets added since the last load. Therefore, the approach reduces the time and resources needed for updating large datasets, promptly making the latest data available. It further strengthens real-time data analytics, where information changes regularly, allowing analysts to access the most recent information. Data Protection Implementing strong data security and governance is a critical data warehousing strategy. This strategy includes measures like role-based access control (RBAC), which limits who views the data. Such measures ensure high data integrity and safeguard it against unauthorized breaches or access. Furthermore, compliance with data laws and rules ensures that sensitive information is protected and best practices are adhered to. Query Enhancement The query optimization technique includes effectively organizing queries or questions so that maximum benefits may be derived from partitions, indexes, and materialized views that store precomputed results. The strategy benefits businesses by expediting query processing, allowing users to promptly get their answers, enhancing user experience, and facilitating complex analytical processes. Data Quality Assurance A prominent data warehousing strategy, data quality assurance relates to maintaining data accuracy, reliability, and conciseness. This involves various crucial measures, such as data examination, validation, and cleaning, which aim to mitigate errors that can influence analysis and decision-making. Such measures not only promise dependable findings but also result in optimal decisions. Data Presentation and Reporting A cloud data warehouse helps users make data-backed decisions and build their own dashboards and reports by converting complex data into valuable insights. Therefore, data presentation and reporting as a strategy help companies leverage business intelligence to ensure sound decisions and goal attainment. 4. Top Data Warehouse Software Vendors Offering Analytics Prowess Empowering businesses with spectacular analytics capabilities, the leading data warehouse software vendors ensure smarter decisions for companies. Here’s a list of the leading data warehouse software vendors promising robust analytics capabilities to businesses: 4.1 Dremio Dremio is an open, self-service SQL analytics platform provider that expedites time to insight, incorporating data lake adaptability with data warehouse performance. Relied on by leading organizations, the company empowers businesses by rendering seamless BI capabilities and allowing unified analytics across varied environments, like on-premises, hybrid, and cloud, for reduced costs. Furthermore, Dremio significantly boosts data management and ensures optimized data functions by streamlining data integration processes. The company facilitates the transformation of Hadoop workloads for sub-second queries by offering a Unified Lakehouse Platform. Dremio’s impressive features include its support for Apache Iceberg, which enables effective data handling with version control. It also can establish distributed data architectures, securing relevant data delivery across hybrid and cloud environments. From reducing ETL complexity to supporting AI endeavors with speedier data access, the company’s striking platform promises simplified data management and supports frictionless self-service analytics directly on data lakes via SQL Query Engine. 4.2 Starburst Starburst is a pioneering data warehouse software vendor that offers fast and adjustable data access solutions, leveraging the power of Trino, a premier SQL analytics engine. Renowned for its enterprise-grade reliability and promising a high-performance data lakehouse solution, the company aims to help customers overcome expensive, rigid, and slow data access constraints. The company’s platform effectively overcomes data silos problems, supports near real-time analytics, and adds to Trino’s capabilities by including tools to connect with diverse data sources, providing 24/7 support, and ensuring robust security. Starburst optimizes data management across traditional (on-premises) and cloud environments through its comprehensive products and features. For instance, the Starburst Galaxy multi-cloud platform allows users to leverage data warehouse-like performance and flexibility. Providing high-efficiency SQL queries directly on the data lake and built-in components for cluster management, data governance, etc., it allows businesses to optimize data analytics processes. Moreover, the Starburst Enterprise platform empowers organizations to link to any data source, employing advanced analytics tools for effective data analysis without data movement. The company notably supports AI workloads at vast scales and provides resilient query processing across multiple data sources, enhancing functional productivity. 4.3 Firebolt Founded in 2019, Firebolt has emerged as a global leader in the cloud data warehouse field and aims to broaden access to robust data analysis tools for more users. Promoting a culture of transparency, responsibility, and customer obsession, the company delivers a leading-edge cloud-based data warehouse platform that incorporates the swiftness of a query accelerator and the ability to handle large volumes of information like a traditional data warehouse. Imperatively, the company strives to empower businesses by streamlining data engineering, amplifying performance, and reducing costs. The company renders spectacular features, transforming cloud data warehousing with low-latency analytics for high concurrency and more agile query responses. With components like distributed multi-threading, data processing in arrays or batches, and an innovative optimizer for more effective execution plans, Firebolt facilitates agile and accurate data operations. The company further ensures ACID compliance, securing data integrity and reliability in database transactions. Additionally, it allows scaling both horizontally and vertically, enabling businesses to handle varying data volumes. Furthermore, the company’s platform encourages active collaborations and remains prepared for continuous integration and continuous deployment practices, supporting automated testing and frictionless updates to data pipelines. 4.4 Lyftrondata Providing a leading-edge data fabric platform, Lyftrondata empowers companies to convert data silos into valuable insights with promptness. Its self-service, agile data-delivery platform includes prominent offerings, such as Data Virtualization, a Managed Warehouse supported by Snowflake, a Data Pipeline, an API Data Hub, a Data Catalog, etc. The company facilitates effortless data integration across varied sources to expedite business insights, leveraging more than 300 connectors and further ensuring HIPAA compliance. Lyftrondata provides a unified environment, allowing users of different technical abilities to manage ETL processes seamlessly. From automating data retrieval to transforming complex data into actionable insights, the company’s forward-thinking platform eliminates manual coding. It employs flexible technologies, such as Kafka streaming and Apache Spark, to ensure easy automation for data integration and processing. The company boasts one of the best data warehouse solutions, empowering users to carry out large-scale analytics. It further leverages data virtualization to speed up live analytics and optimizes data governance, securing data privacy and adhering to enterprise-level security standards. 4.5 CData Standing at the forefront of data access and connectivity solutions, CData aims to simplify data connection processes for organizations and applications in today’s business world, where data is spread out in multiple locations. With real-time connectivity solutions, the company, hence, breaks down and converts data silos, allowing easy access, integration, and sharing of data. The company’s platform boosts businesses’ efficiency by standardizing interactions for operational consistency and optimizes performance at the socket level. It further supports two modes of integration, replicated and live data, and renders real-time data access to users across varied enterprise applications like ERP or CRM systems. CData’s remarkable offerings include CData Virtuality, which enables companies to get immediate access to over 200 data sources and leverage enterprise data virtualization through a consolidated interface to utilize data from varied origins. It further optimizes query performance with caching mechanisms. Another prominent tool, CData Sync, simplifies the creation and implementation of ETL or ELT data pipelines, facilitating the multi-environment deployment of data integration techniques and strategies, offering a cost-effective approach to data replication with its connector-based pricing model, and supporting a broad selection of data origins. Through secure, centralized data management, CData reduces data breaches, backs extensive integrations, and offers self-service connectivity, enhancing decision-making. 4.6 Zap Streamlining data handling for businesses, Zap efficiently integrates data from diverse sources, enriches it, and ensures that it is prepared for analysis. With its innovative Power BI analytic tool or patented Data Hub Analytics, Zap empowers companies to handle their functional and financial analytics requirements effortlessly. The company further leverages pre-defined data models enhanced with specialized knowledge to expedite the data preparation processes and attain actionable insights. The platform’s users can choose between Power BI or the proprietary Zap Data Hub Analytics for all-inclusive business and financial analysis, while Zap augments their capabilities through extensive training. Among the chief features of the company’s platform remain the advanced data modeling options, which include pre-built solutions for ERP systems and a codeless UI with SQL abilities. From boosting analytics with self-detected measures through semantic layer modeling to offering user-friendly dashboards and printable reports, Zap ensures exponential improvement in data and decision-making processes for businesses. 4.7 Druid Catalyzing powerful digital transformation, Druid is an ingenious technology company that specializes in data and analytics. The company employs advanced technologies like artificial intelligence, machine learning, and IoT to help businesses streamline and monitor their operational processes. The company’s services include IoT analytics, serverless frameworks, digital acceleration, and complex integrations. In addition to providing thorough data analysis, Druid further facilitates cloud migration for businesses, amplifying their agility, resource management, and operational prowess. It effectively supports incorporating and managing IoT solutions in the cloud and boasts commendable expertise in designing big data architecture. The company’s promising platform renders intelligent insights to businesses by integrating AI and ML technologies, ensuring boosted productivity and strategic growth. Importantly, Druid’s platform promises agile solutions for businesses, integrating via APIs, optimizing IT project lifecycles, and emphasizing digital advancement. 4.8 TimeXtender TimeXtender embraces innovation and sustainability to streamline data integration techniques and strategies for businesses. Leveraging metadata-driven solutions, it empowers companies to make strategically sound decisions, establishes benchmarks, and keeps a focus on both social and environmental impact. With its powerful and responsive data infrastructure, the company optimizes AI and analytics endeavors of businesses, enabling them to maximize the utmost potential of data. The core functionalities offered by TimeXtender include Master Data Management, which automates data correction, creates hierarchical relationships among critical data entities, and handles reference data, augmenting data governance capabilities. Its platform further ensures excellent data integration, supporting more than 250 pre-configured connectors, entailing incremental loading, and reducing processing times. Furthermore, with its premier Unified Metadata Framework, it facilitates automated code generation for consistent data workflows and supports a shared semantic layer for congruous understanding and usage of data across different departments. Not to mention, the company amplifies data accuracy with its striking data quality management tools for continual evaluation and easy troubleshooting. 4.9 dbt Labs A leader in the data development field, dbt Labs empowers data analysts to amplify data product delivery, ensuring preciseness and reliability in results. Trusted by industry leaders, the company strives to limit the use of dated tools to elevate data confidence and faster operations. From encouraging self-serve data analysis to superlative data oversight, the company stays resolute in its commitment to limit costs and optimize data models. With its robust end-to-end platform, dbt Cloud, it adopts an SQL-first workflow and empowers teams to handle intricate data tasks effortlessly, following best practices in data development and securing high-quality data delivery. From enabling the creation of modular analytics code to automated code testing, the advanced platform ensures result accuracy. It further boasts impressive documentation capabilities, promotes uniform metrics with dbt Semantic Layer, incorporates Git-enabled version control for uniformity, and provides robust security with advanced features. Moreover, offering dbt Explorer, it lets users visualize data transformation lineage, fostering trust, transparency, and reliability in data-backed decisions. 4.10 Redwood Software Redwood Software is a renowned automation platform provider that empowers businesses to automate their processes securely across on-premises and cloud environments. Focused on augmenting enterprise productivity, the company provides impressive cloud-native solutions, allowing integrations for ERP systems and incorporating REST web services via user-friendly API wizards. Serving as a cost-effective choice for businesses’ automation requirements, it provides a consumption-based or pay-as-you-go pricing model to mitigate financial risks and support budget management. The company’s leading-edge platform, RunMyJobs, offers comprehensive features for data warehouse management, allowing businesses to extract valuable insights from big data across departments. The platform ensures proactive data management by enabling automated data extraction from any database and enhancing live data pipeline monitoring via a unified interface. The platform further emphasizes security and optimizes resource management with dynamic load balancing. Such an approach allows strong data governance and promises precision and agility in data processes. 5. Final Thoughts Cloud data warehouses have transformed data processes, strengthening businesses with prompt data access, spectacular analytics capabilities, cost-effectiveness, and unmatched scalability. By partnering with the leading data warehouse software providers, companies today leverage advanced tools to attain crucial insights, drive intelligent decision-making, and achieve operational excellence. With the continual adoption of these advanced technologies, the future of cloud data warehouses is poised to witness continued incorporation of machine learning and artificial intelligence in cloud data warehousing processes. This would effectively automate data-handling tasks and augment predictive analytics for business implementation. The advancement would further witness an inclination toward containerized implementation, exhaustive data governance features, and deployment of microservices architecture. Such changes would equip companies with leading-edge tools to retrieve deeper data insights, enhance innovation, and maximize profitability.

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Cloud Security, Cloud App Management, Cloud Infrastructure Management

What Is Cloud-Native and Why Does it Matter for CI

Article | August 1, 2023

Continuous intelligence (CI) relies on the real-time analysis of streaming data to produce actionable insights in milliseconds to seconds. Such capabilities have applications throughout a business. In today’s dynamic marketplace, new CI applications that use data from various sources at any given time might be needed on very short notice.The challenge is how to have the flexibility to rapidly develop and deploy new CI applications to meet fast-changing business requirements. A common approach employed today is to use a dynamic architecture that delivers access to data, processing power, and analytics capabilities on demand. In the future, solutions also will likely incorporate artificial intelligence applications to complement the benefits of traditional analytics. Increasingly, cloud-native is the architecture of choice to build and deploy AI-embedded CI applications. A cloud-native approach offers benefits to both the business and developers. Cloud-native applications or services are loosely coupled with explicitly described dependencies.

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Cloud Security, Cloud App Management, AWS Management

Why Microsoft Should Spinoff Its Cloud Business

Article | August 14, 2023

Microsoft currently features old-school solutions that are growing relatively slowly (Office and Windows) and new cloud solutions that are growing tremendously (Dynamics 365 and Azure). If the company stays in its current form, Microsoft stock will keep steadily advancing. But because the company’s total top and bottom lines are never going to increase much more than 30% or 35% per year, the shares are never going to deliver truly huge returns. But that would change if the company was to spin off its rapidly growing cloud businesses. In such a scenario, the current owners of Microsoft stock would receive shares in a cutting edge cloud services company (let’s call it Azure), and shares in a company focused on providing old, mostly PC-based software to businesses and consumers.

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Intelligence Giant Upgrading its Cloud Technology

Article | February 10, 2020

With the huge amounts of data in all fields, a future in the cloud is imperative to help deal with this explosion of data, especially in the field of intelligence technology. This is the reason why the US Central Intelligence Agency is updating its cloud technology. The agency has recently released a draft request for proposal for its Commercial Cloud Enterprise contract.The C2E tens of billions contract will be a multi-award commercial cloud computing contract with a five-year base period and two five-year options for a period of performance of up to 15 years, according to nextgov.com.In a March 2019 presentation by the Directorate of Digital Innovation, a division of the CIA, the department outlined its vision for C2E. It would be broad and include infrastructure, platform and software cloud services supporting a broad range of users, with a variety of security clearances and a worldwide presence, as reported by techcrunch.com. The principal C2E Program objective is to acquire cloud computing services directly from commercial cloud service providers with established records for innovation and operational excellence in cloud service delivery for a large customer base,the department stated in the presentation.Apparently, the agency prefers to avoid all the attention that the Pentagon’s JEDI cloud procurement process got, and quietly go about its business.

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Cloud Security, Cloud App Management, Cloud Infrastructure Management

3 Hybrid Cloud Security Strategies for Managing Privileged Access

Article | July 27, 2023

From amplified scalability to data transparency, top data warehouse software vendors boost businesses’ analysis capabilities. Learn how companies gain data agility with cloud data warehouse software. Contents 1. Understanding the Fundamentals of a Cloud Data Warehouse 2. Key Advantages of Data Warehousing for Businesses 3. Data Warehouse Strategies to Integrate and Analyze Data 4. Top Data Warehouse Software Vendors Offering Analytics Prowess 4.1 Dremio 4.2 Starburst 4.3 Firebolt 4.4 Lyftrondata 4.5 CData 4.6 Zap 4.7 Druid 4.8 TimeXtender 4.9 dbt Labs 4.10 Redwood Software 5. Final Thoughts 1. Understanding the Fundamentals of a Cloud Data Warehouse Representing a robust solution for handling and storing vast datasets, a cloud data warehouse offers businesses high convenience, quick data access, and remarkable flexibility. The data warehouse is essentially hosted in a cloud computing environment that empowers organizations to modify storage and processing as and when required without needing hardware upgrades. The growing prominence of the advanced setup today can notably be ascribed to its unparalleled accessibility, which allows companies to manage their data from any part of the world via internet access. Likewise, the warehouse’s core components include a centralized repository with distinct computing abilities, which enable scalable data retention and optimized resource allocation. Moreover, the data warehouse software boasts phenomenal data integration and handling tools, allowing businesses to link to diverse data sources, build datasets, set permissions, and run queries. It further boosts companies’ performances through parallel query processing, system backups, data encryption, etc. Moreover, supporting innovative analytics and insights, the cloud environment enables businesses to make data-backed decisions, augmenting their analytics prowess and driving high ROIs. 2. Key Advantages of Data Warehousing for Businesses From enhanced financial efficiencies to unmatched data access, data warehousing practices offer multiple benefits to businesses that allow sound decision-making and operational success. The chief merits of a data warehouse software include: Scalable Infrastructure for Unhindered Productivity With a cloud data warehouse, businesses can effortlessly adjust resources to handle diverse data processing requirements and scale up or down without bearing upgrade costs ascribed to traditional on-premises systems. By simply modifying payment schemes, companies can increase or decrease their computing power or storage, paying only for what they use. The unparalleled scalability further enables businesses to ensure undisturbed operations, faster innovations, and speed-to-market, benefiting from high agility in operations and augmenting business productivity. Quick Data Access Cloud data warehouses enhance data availability exponentially. They unify diverse data into a centralized repository, enabling users to access data quickly from anywhere in the world via web access. This flexible access, in turn, encourages remote work and collaboration endeavors, promoting real-time decision-making and augmenting operational responsiveness. Enhanced Visual Data Analysis With leading-edge business intelligence tools, advanced data warehouses support swift data processing, empowering businesses to extract crucial insights and analyze data in real time. The boosted analytics and data visualization abilities help companies make sound decisions and stay ahead of the curve. Cost-effectiveness A cloud data warehouse is a more economical substitute for on-premises systems. It works on a pay-as-you-go model, eliminating the need for physical hardware. Therefore, companies pay only for the computing resources and storage they use. Most data warehouse providers offer flexible pricing models, enabling businesses to maintain cost-efficient systems for data warehousing. Robust Security and Disaster Recovery A significant advantage of the cloud data warehouse is that it implements notable security measures like access controls, data encryption, and periodic security audits to protect sensitive business data and information from unauthorized breaches. It offers all-inclusive disaster recovery solutions, including scheduled backups and data replication across various geographic locations. Such features secure unhindered functions and data resilience in times of unanticipated interruptions. Performance Excellence Boasting features like distributed computing and parallel processing, cloud data warehouses guarantee elevated business performance as they quicken data analysis and query execution. From optimizing operations through automated tasks to eliminating the need for costly hardware investments, data warehouse setups on the cloud promise boosted productivity and efficiency. Impressive Integrations Cloud data platforms offer impressive integration capabilities, helping businesses connect with various data origins and third-party applications. Such incorporations expedite effective data reporting and analysis and augment businesses’ ability to extract valuable insights, showcasing the advantage of data warehouse integration and leading to better performance. Reliable Support and Ease-of-Use Established cloud data warehouse providers render round-the-clock support to businesses, ensuring uninterrupted operations and prompt problem resolutions. The warehouse, which comprises intuitive user interfaces, simplifies data access for non-technical teams, reducing dependency on IT staff and enabling the autonomous performance of data tasks, such as data reading, editing, and writing, through low-code or codeless platforms. 3. Data Warehouse Strategies to Integrate and Analyze Data Businesses employ various data warehousing techniques and strategies, like ETL or incremental loading, to maintain excellent quality in business processes and secure optimized performance. Here’s a breakdown of the prominent data warehouse strategies that companies leverage to derive crucial insights and gain remarkable scalability: Effective Metadata Categorization With strong metadata categorization, businesses can enhance data extraction and organization, simplifying data queries and augmenting accessibility. The centralized metadata management further documents data usage, lineage, and definitions, facilitating efficient data governance. The strategy helps stakeholders easily find and understand the required data, ensures compliance with data use regulations, and promotes data transparency and availability within the company. ETL Technique for Data Integration Through the ETL processes, i.e., extract, transform, load, data can be retrieved from diverse sources, transformed to match the warehouse schema, and loaded into the target system or data warehouse. This strategy is pivotal for incorporating data into the setup. It effectively streamlines data flows and allows businesses to conduct impactful data analysis. Data Segmentation and Indexing Also called ‘partitioning’, data segmentation involves dividing vast tables into easy-to-manage segments, maximizing data extraction, storage, and management. Each of these segments or ‘partitions’, therefore, holds a subset of the large table’s data, divided according to established criteria, like hash keys or value ranges. Indexing, likewise, allows speedy data retrieval based on specific criteria, as it creates systematized lists of the table’s fundamental values. Collectively, these promising strategies optimize query processing and database management, ensuring responsiveness with increasing data volumes. Data Modeling Strategy Data can be organized effectively for optimum querying by leveraging techniques like star or snowflake schemas. For instance, measurable data like sales can be stored in fact tables, while attributes like time or location are stored in dimension tables. Hence, the data modeling strategy makes it simpler to ask intricate questions about data, boosting performance and enabling easy-to-understand data analysis and exploration. Incremental Loading for Quicker Data Processing Another prominent data warehousing strategy is incremental loading. This strategy involves speeding up information handling processes by only making changes since the last data update. While the previous data remains unchanged, only new data gets added since the last load. Therefore, the approach reduces the time and resources needed for updating large datasets, promptly making the latest data available. It further strengthens real-time data analytics, where information changes regularly, allowing analysts to access the most recent information. Data Protection Implementing strong data security and governance is a critical data warehousing strategy. This strategy includes measures like role-based access control (RBAC), which limits who views the data. Such measures ensure high data integrity and safeguard it against unauthorized breaches or access. Furthermore, compliance with data laws and rules ensures that sensitive information is protected and best practices are adhered to. Query Enhancement The query optimization technique includes effectively organizing queries or questions so that maximum benefits may be derived from partitions, indexes, and materialized views that store precomputed results. The strategy benefits businesses by expediting query processing, allowing users to promptly get their answers, enhancing user experience, and facilitating complex analytical processes. Data Quality Assurance A prominent data warehousing strategy, data quality assurance relates to maintaining data accuracy, reliability, and conciseness. This involves various crucial measures, such as data examination, validation, and cleaning, which aim to mitigate errors that can influence analysis and decision-making. Such measures not only promise dependable findings but also result in optimal decisions. Data Presentation and Reporting A cloud data warehouse helps users make data-backed decisions and build their own dashboards and reports by converting complex data into valuable insights. Therefore, data presentation and reporting as a strategy help companies leverage business intelligence to ensure sound decisions and goal attainment. 4. Top Data Warehouse Software Vendors Offering Analytics Prowess Empowering businesses with spectacular analytics capabilities, the leading data warehouse software vendors ensure smarter decisions for companies. Here’s a list of the leading data warehouse software vendors promising robust analytics capabilities to businesses: 4.1 Dremio Dremio is an open, self-service SQL analytics platform provider that expedites time to insight, incorporating data lake adaptability with data warehouse performance. Relied on by leading organizations, the company empowers businesses by rendering seamless BI capabilities and allowing unified analytics across varied environments, like on-premises, hybrid, and cloud, for reduced costs. Furthermore, Dremio significantly boosts data management and ensures optimized data functions by streamlining data integration processes. The company facilitates the transformation of Hadoop workloads for sub-second queries by offering a Unified Lakehouse Platform. Dremio’s impressive features include its support for Apache Iceberg, which enables effective data handling with version control. It also can establish distributed data architectures, securing relevant data delivery across hybrid and cloud environments. From reducing ETL complexity to supporting AI endeavors with speedier data access, the company’s striking platform promises simplified data management and supports frictionless self-service analytics directly on data lakes via SQL Query Engine. 4.2 Starburst Starburst is a pioneering data warehouse software vendor that offers fast and adjustable data access solutions, leveraging the power of Trino, a premier SQL analytics engine. Renowned for its enterprise-grade reliability and promising a high-performance data lakehouse solution, the company aims to help customers overcome expensive, rigid, and slow data access constraints. The company’s platform effectively overcomes data silos problems, supports near real-time analytics, and adds to Trino’s capabilities by including tools to connect with diverse data sources, providing 24/7 support, and ensuring robust security. Starburst optimizes data management across traditional (on-premises) and cloud environments through its comprehensive products and features. For instance, the Starburst Galaxy multi-cloud platform allows users to leverage data warehouse-like performance and flexibility. Providing high-efficiency SQL queries directly on the data lake and built-in components for cluster management, data governance, etc., it allows businesses to optimize data analytics processes. Moreover, the Starburst Enterprise platform empowers organizations to link to any data source, employing advanced analytics tools for effective data analysis without data movement. The company notably supports AI workloads at vast scales and provides resilient query processing across multiple data sources, enhancing functional productivity. 4.3 Firebolt Founded in 2019, Firebolt has emerged as a global leader in the cloud data warehouse field and aims to broaden access to robust data analysis tools for more users. Promoting a culture of transparency, responsibility, and customer obsession, the company delivers a leading-edge cloud-based data warehouse platform that incorporates the swiftness of a query accelerator and the ability to handle large volumes of information like a traditional data warehouse. Imperatively, the company strives to empower businesses by streamlining data engineering, amplifying performance, and reducing costs. The company renders spectacular features, transforming cloud data warehousing with low-latency analytics for high concurrency and more agile query responses. With components like distributed multi-threading, data processing in arrays or batches, and an innovative optimizer for more effective execution plans, Firebolt facilitates agile and accurate data operations. The company further ensures ACID compliance, securing data integrity and reliability in database transactions. Additionally, it allows scaling both horizontally and vertically, enabling businesses to handle varying data volumes. Furthermore, the company’s platform encourages active collaborations and remains prepared for continuous integration and continuous deployment practices, supporting automated testing and frictionless updates to data pipelines. 4.4 Lyftrondata Providing a leading-edge data fabric platform, Lyftrondata empowers companies to convert data silos into valuable insights with promptness. Its self-service, agile data-delivery platform includes prominent offerings, such as Data Virtualization, a Managed Warehouse supported by Snowflake, a Data Pipeline, an API Data Hub, a Data Catalog, etc. The company facilitates effortless data integration across varied sources to expedite business insights, leveraging more than 300 connectors and further ensuring HIPAA compliance. Lyftrondata provides a unified environment, allowing users of different technical abilities to manage ETL processes seamlessly. From automating data retrieval to transforming complex data into actionable insights, the company’s forward-thinking platform eliminates manual coding. It employs flexible technologies, such as Kafka streaming and Apache Spark, to ensure easy automation for data integration and processing. The company boasts one of the best data warehouse solutions, empowering users to carry out large-scale analytics. It further leverages data virtualization to speed up live analytics and optimizes data governance, securing data privacy and adhering to enterprise-level security standards. 4.5 CData Standing at the forefront of data access and connectivity solutions, CData aims to simplify data connection processes for organizations and applications in today’s business world, where data is spread out in multiple locations. With real-time connectivity solutions, the company, hence, breaks down and converts data silos, allowing easy access, integration, and sharing of data. The company’s platform boosts businesses’ efficiency by standardizing interactions for operational consistency and optimizes performance at the socket level. It further supports two modes of integration, replicated and live data, and renders real-time data access to users across varied enterprise applications like ERP or CRM systems. CData’s remarkable offerings include CData Virtuality, which enables companies to get immediate access to over 200 data sources and leverage enterprise data virtualization through a consolidated interface to utilize data from varied origins. It further optimizes query performance with caching mechanisms. Another prominent tool, CData Sync, simplifies the creation and implementation of ETL or ELT data pipelines, facilitating the multi-environment deployment of data integration techniques and strategies, offering a cost-effective approach to data replication with its connector-based pricing model, and supporting a broad selection of data origins. Through secure, centralized data management, CData reduces data breaches, backs extensive integrations, and offers self-service connectivity, enhancing decision-making. 4.6 Zap Streamlining data handling for businesses, Zap efficiently integrates data from diverse sources, enriches it, and ensures that it is prepared for analysis. With its innovative Power BI analytic tool or patented Data Hub Analytics, Zap empowers companies to handle their functional and financial analytics requirements effortlessly. The company further leverages pre-defined data models enhanced with specialized knowledge to expedite the data preparation processes and attain actionable insights. The platform’s users can choose between Power BI or the proprietary Zap Data Hub Analytics for all-inclusive business and financial analysis, while Zap augments their capabilities through extensive training. Among the chief features of the company’s platform remain the advanced data modeling options, which include pre-built solutions for ERP systems and a codeless UI with SQL abilities. From boosting analytics with self-detected measures through semantic layer modeling to offering user-friendly dashboards and printable reports, Zap ensures exponential improvement in data and decision-making processes for businesses. 4.7 Druid Catalyzing powerful digital transformation, Druid is an ingenious technology company that specializes in data and analytics. The company employs advanced technologies like artificial intelligence, machine learning, and IoT to help businesses streamline and monitor their operational processes. The company’s services include IoT analytics, serverless frameworks, digital acceleration, and complex integrations. In addition to providing thorough data analysis, Druid further facilitates cloud migration for businesses, amplifying their agility, resource management, and operational prowess. It effectively supports incorporating and managing IoT solutions in the cloud and boasts commendable expertise in designing big data architecture. The company’s promising platform renders intelligent insights to businesses by integrating AI and ML technologies, ensuring boosted productivity and strategic growth. Importantly, Druid’s platform promises agile solutions for businesses, integrating via APIs, optimizing IT project lifecycles, and emphasizing digital advancement. 4.8 TimeXtender TimeXtender embraces innovation and sustainability to streamline data integration techniques and strategies for businesses. Leveraging metadata-driven solutions, it empowers companies to make strategically sound decisions, establishes benchmarks, and keeps a focus on both social and environmental impact. With its powerful and responsive data infrastructure, the company optimizes AI and analytics endeavors of businesses, enabling them to maximize the utmost potential of data. The core functionalities offered by TimeXtender include Master Data Management, which automates data correction, creates hierarchical relationships among critical data entities, and handles reference data, augmenting data governance capabilities. Its platform further ensures excellent data integration, supporting more than 250 pre-configured connectors, entailing incremental loading, and reducing processing times. Furthermore, with its premier Unified Metadata Framework, it facilitates automated code generation for consistent data workflows and supports a shared semantic layer for congruous understanding and usage of data across different departments. Not to mention, the company amplifies data accuracy with its striking data quality management tools for continual evaluation and easy troubleshooting. 4.9 dbt Labs A leader in the data development field, dbt Labs empowers data analysts to amplify data product delivery, ensuring preciseness and reliability in results. Trusted by industry leaders, the company strives to limit the use of dated tools to elevate data confidence and faster operations. From encouraging self-serve data analysis to superlative data oversight, the company stays resolute in its commitment to limit costs and optimize data models. With its robust end-to-end platform, dbt Cloud, it adopts an SQL-first workflow and empowers teams to handle intricate data tasks effortlessly, following best practices in data development and securing high-quality data delivery. From enabling the creation of modular analytics code to automated code testing, the advanced platform ensures result accuracy. It further boasts impressive documentation capabilities, promotes uniform metrics with dbt Semantic Layer, incorporates Git-enabled version control for uniformity, and provides robust security with advanced features. Moreover, offering dbt Explorer, it lets users visualize data transformation lineage, fostering trust, transparency, and reliability in data-backed decisions. 4.10 Redwood Software Redwood Software is a renowned automation platform provider that empowers businesses to automate their processes securely across on-premises and cloud environments. Focused on augmenting enterprise productivity, the company provides impressive cloud-native solutions, allowing integrations for ERP systems and incorporating REST web services via user-friendly API wizards. Serving as a cost-effective choice for businesses’ automation requirements, it provides a consumption-based or pay-as-you-go pricing model to mitigate financial risks and support budget management. The company’s leading-edge platform, RunMyJobs, offers comprehensive features for data warehouse management, allowing businesses to extract valuable insights from big data across departments. The platform ensures proactive data management by enabling automated data extraction from any database and enhancing live data pipeline monitoring via a unified interface. The platform further emphasizes security and optimizes resource management with dynamic load balancing. Such an approach allows strong data governance and promises precision and agility in data processes. 5. Final Thoughts Cloud data warehouses have transformed data processes, strengthening businesses with prompt data access, spectacular analytics capabilities, cost-effectiveness, and unmatched scalability. By partnering with the leading data warehouse software providers, companies today leverage advanced tools to attain crucial insights, drive intelligent decision-making, and achieve operational excellence. With the continual adoption of these advanced technologies, the future of cloud data warehouses is poised to witness continued incorporation of machine learning and artificial intelligence in cloud data warehousing processes. This would effectively automate data-handling tasks and augment predictive analytics for business implementation. The advancement would further witness an inclination toward containerized implementation, exhaustive data governance features, and deployment of microservices architecture. Such changes would equip companies with leading-edge tools to retrieve deeper data insights, enhance innovation, and maximize profitability.

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Cloud Security, Cloud App Management, Cloud Infrastructure Management

Top 10 Cloud Security Management Tools for 2023

Article | August 1, 2023

Continuous intelligence (CI) relies on the real-time analysis of streaming data to produce actionable insights in milliseconds to seconds. Such capabilities have applications throughout a business. In today’s dynamic marketplace, new CI applications that use data from various sources at any given time might be needed on very short notice.The challenge is how to have the flexibility to rapidly develop and deploy new CI applications to meet fast-changing business requirements. A common approach employed today is to use a dynamic architecture that delivers access to data, processing power, and analytics capabilities on demand. In the future, solutions also will likely incorporate artificial intelligence applications to complement the benefits of traditional analytics. Increasingly, cloud-native is the architecture of choice to build and deploy AI-embedded CI applications. A cloud-native approach offers benefits to both the business and developers. Cloud-native applications or services are loosely coupled with explicitly described dependencies.

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Cloud Security, Cloud App Management, AWS Management

Top 15 Cloud Security Certifications to Grow Your Career in Cloud Security

Article | August 14, 2023

Microsoft currently features old-school solutions that are growing relatively slowly (Office and Windows) and new cloud solutions that are growing tremendously (Dynamics 365 and Azure). If the company stays in its current form, Microsoft stock will keep steadily advancing. But because the company’s total top and bottom lines are never going to increase much more than 30% or 35% per year, the shares are never going to deliver truly huge returns. But that would change if the company was to spin off its rapidly growing cloud businesses. In such a scenario, the current owners of Microsoft stock would receive shares in a cutting edge cloud services company (let’s call it Azure), and shares in a company focused on providing old, mostly PC-based software to businesses and consumers.

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Intelligence Giant Upgrading its Cloud Technology

Article | February 10, 2020

With the huge amounts of data in all fields, a future in the cloud is imperative to help deal with this explosion of data, especially in the field of intelligence technology. This is the reason why the US Central Intelligence Agency is updating its cloud technology. The agency has recently released a draft request for proposal for its Commercial Cloud Enterprise contract.The C2E tens of billions contract will be a multi-award commercial cloud computing contract with a five-year base period and two five-year options for a period of performance of up to 15 years, according to nextgov.com.In a March 2019 presentation by the Directorate of Digital Innovation, a division of the CIA, the department outlined its vision for C2E. It would be broad and include infrastructure, platform and software cloud services supporting a broad range of users, with a variety of security clearances and a worldwide presence, as reported by techcrunch.com. The principal C2E Program objective is to acquire cloud computing services directly from commercial cloud service providers with established records for innovation and operational excellence in cloud service delivery for a large customer base,the department stated in the presentation.Apparently, the agency prefers to avoid all the attention that the Pentagon’s JEDI cloud procurement process got, and quietly go about its business.

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Cloud Infrastructure Management

The Manufacturing Sector Experiences More Attacks in the Cloud than Any Other Industry

PR Newswire: | January 19, 2024

Netwrix, a cybersecurity vendor that makes data security easy, today revealed additional findings for the manufacturing sector from its survey of 1,610 IT and security professionals across more than 100 countries. According to the survey, 64% of companies in the manufacturing sector suffered a cyberattack during the preceding 12 months, which is similar to the finding among organizations overall (68%). However, it turned out that the manufacturing sector experiences more cloud infrastructure attacks than any other industry surveyed. Among manufacturing companies that detected an attack, 85% spotted phishing in the cloud compared to only 58% across all verticals; 43% faced user account compromise in the cloud as opposed to 27% among all industries; and 25% dealt with data theft by hackers in the cloud compared to 15% for organizations overall. "The manufacturing sector relies heavily on the cloud to work with their supply chain in real time. This makes their cloud infrastructure a lucrative target for attackers — infiltrating it enables them to move laterally and potentially compromise other linked organizations, as happened to one the world's top meat processing companies. Credential compromise or malware deployed via a phishing email is just the beginning of the attack," says Dirk Schrader, VP of Security Research at Netwrix. "The attack surface in the cloud is always expanding, so it's critical for manufacturing companies to adopt a defense-in-depth approach," adds Ilia Sotnikov, Security Strategist at Netwrix. "First, they must rigorously enforce the principle of least privilege to limit access to sensitive data, which ideally includes just-in-time access to eliminate unnecessary entry points for adversaries. They also need to gain deep visibility into when and how critical data in the cloud is being used so that IT teams can promptly spot potential threats. Finally, they need to be prepared to minimize the damage from incidents by having a comprehensive response strategy that is regularly exercised and updated." To learn more about security trends, check out the complete 2023 Hybrid Security Trends Report. About Netwrix Netwrix makes data security easy. Since 2006, Netwrix solutions have been simplifying the lives of security professionals by enabling them to identify and protect sensitive data to reduce the risk of a breach, and to detect, respond to and recover from attacks, limiting their impact. More than 13,500 organizations worldwide rely on Netwrix solutions to strengthen their security and compliance posture across all three primary attack vectors: data, identity and infrastructure.

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Cloud Storage

TRG Screen Announces Acquisition of Xpansion for Reference Data Usage Management

PR Newswire: | January 25, 2024

TRG Screen, the leading provider of enterprise subscription spend and usage management software, today announced it has acquired Xpansion, the leading provider of cloud-based solutions for reference data usage monitoring in the financial services industry. The acquisition of Xpansion will further solidify TRG Screen's position as a global market leader in market data management solutions. Xpansion – established in 2013 – is focused on empowering data operations teams to proactively manage their usage, control costs and optimize data workflows. Xpansion's offerings include Xmon, Xprocess and Xplore, and provide real-time analytics, giving clients unprecedented transparency, visibility and control into their reference data usage. This deal consolidates TRG Screen's unique position as the only provider of enterprise subscription management capabilities spanning the whole spectrum of market data optimization, from spend and inventory tracking, through to usage and enquiry management, exchange reporting and compliance. "Xpansion and TRG Screen have been partners for many years. Bringing Xpansion into the TRG Screen family is a very logical next step for both companies, given our strong relationship and shared view that the industry demand for integrated usage management solutions is going to continue to grow," said TRG Screen CEO Leigh Walters. "Xpansion is an established firm with excellent customer satisfaction and retention, and highly experienced and industry respected leadership. We are very excited at the opportunities this acquisition brings." "We are thrilled to be joining TRG Screen," said Xpansion co-founder and CEO Amjad Zoghbi. "Reference data usage is one of the most complex aspects of market data management, and managing it correctly is essential to maintaining contractual compliance and ensuring clients are right-sizing their usage based on actual consumption and business need. I'm very pleased that Xpansion's customers, and team, will now be part of the best-of-breed solution with the industry's leading provider of market data management solutions." The acquisition demonstrates TRG Screen's ongoing commitment to servicing the needs of market data consumers, vendors and exchanges. Financial terms of the transaction were not disclosed. About TRG Screen TRG Screen is the leading provider of enterprise subscription management solutions. Founded in 1998, TRG Screen is uniquely differentiated by its ability to monitor both spend and usage of data and information services including market data, research, software licenses, consulting and other corporate expenses. TRG Screen's solutions provide its customers with full transparency into their vendor relationships and their subscription spend and usage, enabling them to optimize their enterprise subscriptions. TRG acquired Priory Solutions in 2016, Screen Group in 2018, Axon Financial Systems in 2019, Market Data Insights in 2020, and Jordan & Jordan's Market Data Reporting (MDR) business in 2021 and with these acquisitions is now positioned as the global market leader in the financial, legal, and professional services markets. TRG Screen's product portfolio includes subscription spend, usage, enquiry and compliance solutions. For more information visit trgscreen.com. Follow TRG Screen on LinkedIn, @TRG Screen, and on Twitter, @trgscreen. About Xpansion Xpansion delivers next-generation reference data solutions that empower financial institutions to streamline their reference data operations, reduce costs, enhance data quality, and improve data discovery. With a focus on customer satisfaction, continuous innovation and quick time to value, Xpansion is a trusted partner for financial institutions in the buy- and sell-side as well as solution providers in the industry.

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Cloud App Management

DriveNets and Acacia Announce Joint Network Cloud 400G ZR/ZR+ Solution

PR Newswire | January 16, 2024

DriveNets – a leader in innovative networking solutions – and Acacia today announced the completion of integrating multiple Acacia 400G ZR/ZR+ optical modules with DriveNets' Network Cloud platform. The combined DriveNets-Acacia solution will ensure quick adoption of this innovative disaggregated networking solution and accelerate large-scale network rollouts. DriveNets and Acacia have joint Tier-1 operator customers who will deploy the joint solution. Last September, DriveNets announced that Network Cloud was the first Disaggregated Distributed Chassis/Backbone Router (DDC/DDBR) to support ZR/ZR+ optics as native transceivers that can be inserted into any Network Cloud-supported white boxes. The combined Acacia-DriveNets solution announced today adds the initial collaboration between the companies, offering several benefits: The joint solution will deliver significant simplicity and cost savings by collapsing Layer-1 to Layer-3 communications into a single platform. The use of 400ZR/ZR+ eliminates the need for standalone optical transponders, lowering the number of boxes in the solution, and reducing operational-overhead, floor-space, and power. DriveNets and Acacia worked together to ensure that the DriveNets NOS (DNOS) supports the 400ZR/ZR+ modules beyond simply plugging them into the box. The collaboration ensures the 400ZR/ZR+ modules can be tunable, configurable, and manageable by DriveNets Network Cloud software. This integration also goes beyond interoperability validation. DriveNets Network Cloud offers full software support for the Acacia modules, including configuration (channel and power), monitoring, and troubleshooting for Acacia Bright 400ZR+ transceivers with transmit power greater than +1dBm. "Today's announcement is further proof of the growth of disaggregated networking solutions and demonstrates that more operators are looking for open solutions that will allow them to mix elements from multiple vendors and avoid being locked to a specific end-to-end vendor solution," said Nir Gasko, Vice President, Global Strategic Alliances for DriveNets. "By collaborating with Acacia, we enable our joint customers to quickly adopt cutting-edge technologies and evolve their networks faster." "Partnering with DriveNets on this joint solution will allow network operators to deploy Acacia's high-volume standard-based coherent pluggable portfolio in open disaggregated networks with less effort," said Fenghai Liu, Senior Director of Product Line Management for Acacia. "Through this collaboration customers can achieve significant capex and opex savings with router-based coherent optics." DriveNets Network Cloud is being adopted by more Tier-1 operators around the world. By partnering with world-class providers like Acacia, the company continues to expand its ecosystem to support its customers' desire to mix-and-match hardware and software from multiple vendors. Learn more about DriveNets here. About DriveNets DriveNets is a leader in high-scale disaggregated networking solutions. Founded in 2015, DriveNets modernizes the way service providers, cloud providers and hyperscalers build networks, streamlining network operations, increasing network performance at scale, and improving their economic model. DriveNets' solutions – Network Cloud and Network Cloud-AI – adapt the architectural model of hyperscale cloud to telco-grade networking and support any network use case – from core-to-edge to AI networking – over a shared physical infrastructure of standard white-boxes, radically simplifying the network's operations and offering telco-scale performance and reliability with hyperscale elasticity. DriveNets' solutions are currently deployed in the world's largest networks.

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Cloud Infrastructure Management

The Manufacturing Sector Experiences More Attacks in the Cloud than Any Other Industry

PR Newswire: | January 19, 2024

Netwrix, a cybersecurity vendor that makes data security easy, today revealed additional findings for the manufacturing sector from its survey of 1,610 IT and security professionals across more than 100 countries. According to the survey, 64% of companies in the manufacturing sector suffered a cyberattack during the preceding 12 months, which is similar to the finding among organizations overall (68%). However, it turned out that the manufacturing sector experiences more cloud infrastructure attacks than any other industry surveyed. Among manufacturing companies that detected an attack, 85% spotted phishing in the cloud compared to only 58% across all verticals; 43% faced user account compromise in the cloud as opposed to 27% among all industries; and 25% dealt with data theft by hackers in the cloud compared to 15% for organizations overall. "The manufacturing sector relies heavily on the cloud to work with their supply chain in real time. This makes their cloud infrastructure a lucrative target for attackers — infiltrating it enables them to move laterally and potentially compromise other linked organizations, as happened to one the world's top meat processing companies. Credential compromise or malware deployed via a phishing email is just the beginning of the attack," says Dirk Schrader, VP of Security Research at Netwrix. "The attack surface in the cloud is always expanding, so it's critical for manufacturing companies to adopt a defense-in-depth approach," adds Ilia Sotnikov, Security Strategist at Netwrix. "First, they must rigorously enforce the principle of least privilege to limit access to sensitive data, which ideally includes just-in-time access to eliminate unnecessary entry points for adversaries. They also need to gain deep visibility into when and how critical data in the cloud is being used so that IT teams can promptly spot potential threats. Finally, they need to be prepared to minimize the damage from incidents by having a comprehensive response strategy that is regularly exercised and updated." To learn more about security trends, check out the complete 2023 Hybrid Security Trends Report. About Netwrix Netwrix makes data security easy. Since 2006, Netwrix solutions have been simplifying the lives of security professionals by enabling them to identify and protect sensitive data to reduce the risk of a breach, and to detect, respond to and recover from attacks, limiting their impact. More than 13,500 organizations worldwide rely on Netwrix solutions to strengthen their security and compliance posture across all three primary attack vectors: data, identity and infrastructure.

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Cloud Storage

TRG Screen Announces Acquisition of Xpansion for Reference Data Usage Management

PR Newswire: | January 25, 2024

TRG Screen, the leading provider of enterprise subscription spend and usage management software, today announced it has acquired Xpansion, the leading provider of cloud-based solutions for reference data usage monitoring in the financial services industry. The acquisition of Xpansion will further solidify TRG Screen's position as a global market leader in market data management solutions. Xpansion – established in 2013 – is focused on empowering data operations teams to proactively manage their usage, control costs and optimize data workflows. Xpansion's offerings include Xmon, Xprocess and Xplore, and provide real-time analytics, giving clients unprecedented transparency, visibility and control into their reference data usage. This deal consolidates TRG Screen's unique position as the only provider of enterprise subscription management capabilities spanning the whole spectrum of market data optimization, from spend and inventory tracking, through to usage and enquiry management, exchange reporting and compliance. "Xpansion and TRG Screen have been partners for many years. Bringing Xpansion into the TRG Screen family is a very logical next step for both companies, given our strong relationship and shared view that the industry demand for integrated usage management solutions is going to continue to grow," said TRG Screen CEO Leigh Walters. "Xpansion is an established firm with excellent customer satisfaction and retention, and highly experienced and industry respected leadership. We are very excited at the opportunities this acquisition brings." "We are thrilled to be joining TRG Screen," said Xpansion co-founder and CEO Amjad Zoghbi. "Reference data usage is one of the most complex aspects of market data management, and managing it correctly is essential to maintaining contractual compliance and ensuring clients are right-sizing their usage based on actual consumption and business need. I'm very pleased that Xpansion's customers, and team, will now be part of the best-of-breed solution with the industry's leading provider of market data management solutions." The acquisition demonstrates TRG Screen's ongoing commitment to servicing the needs of market data consumers, vendors and exchanges. Financial terms of the transaction were not disclosed. About TRG Screen TRG Screen is the leading provider of enterprise subscription management solutions. Founded in 1998, TRG Screen is uniquely differentiated by its ability to monitor both spend and usage of data and information services including market data, research, software licenses, consulting and other corporate expenses. TRG Screen's solutions provide its customers with full transparency into their vendor relationships and their subscription spend and usage, enabling them to optimize their enterprise subscriptions. TRG acquired Priory Solutions in 2016, Screen Group in 2018, Axon Financial Systems in 2019, Market Data Insights in 2020, and Jordan & Jordan's Market Data Reporting (MDR) business in 2021 and with these acquisitions is now positioned as the global market leader in the financial, legal, and professional services markets. TRG Screen's product portfolio includes subscription spend, usage, enquiry and compliance solutions. For more information visit trgscreen.com. Follow TRG Screen on LinkedIn, @TRG Screen, and on Twitter, @trgscreen. About Xpansion Xpansion delivers next-generation reference data solutions that empower financial institutions to streamline their reference data operations, reduce costs, enhance data quality, and improve data discovery. With a focus on customer satisfaction, continuous innovation and quick time to value, Xpansion is a trusted partner for financial institutions in the buy- and sell-side as well as solution providers in the industry.

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DriveNets and Acacia Announce Joint Network Cloud 400G ZR/ZR+ Solution

PR Newswire | January 16, 2024

DriveNets – a leader in innovative networking solutions – and Acacia today announced the completion of integrating multiple Acacia 400G ZR/ZR+ optical modules with DriveNets' Network Cloud platform. The combined DriveNets-Acacia solution will ensure quick adoption of this innovative disaggregated networking solution and accelerate large-scale network rollouts. DriveNets and Acacia have joint Tier-1 operator customers who will deploy the joint solution. Last September, DriveNets announced that Network Cloud was the first Disaggregated Distributed Chassis/Backbone Router (DDC/DDBR) to support ZR/ZR+ optics as native transceivers that can be inserted into any Network Cloud-supported white boxes. The combined Acacia-DriveNets solution announced today adds the initial collaboration between the companies, offering several benefits: The joint solution will deliver significant simplicity and cost savings by collapsing Layer-1 to Layer-3 communications into a single platform. The use of 400ZR/ZR+ eliminates the need for standalone optical transponders, lowering the number of boxes in the solution, and reducing operational-overhead, floor-space, and power. DriveNets and Acacia worked together to ensure that the DriveNets NOS (DNOS) supports the 400ZR/ZR+ modules beyond simply plugging them into the box. The collaboration ensures the 400ZR/ZR+ modules can be tunable, configurable, and manageable by DriveNets Network Cloud software. This integration also goes beyond interoperability validation. DriveNets Network Cloud offers full software support for the Acacia modules, including configuration (channel and power), monitoring, and troubleshooting for Acacia Bright 400ZR+ transceivers with transmit power greater than +1dBm. "Today's announcement is further proof of the growth of disaggregated networking solutions and demonstrates that more operators are looking for open solutions that will allow them to mix elements from multiple vendors and avoid being locked to a specific end-to-end vendor solution," said Nir Gasko, Vice President, Global Strategic Alliances for DriveNets. "By collaborating with Acacia, we enable our joint customers to quickly adopt cutting-edge technologies and evolve their networks faster." "Partnering with DriveNets on this joint solution will allow network operators to deploy Acacia's high-volume standard-based coherent pluggable portfolio in open disaggregated networks with less effort," said Fenghai Liu, Senior Director of Product Line Management for Acacia. "Through this collaboration customers can achieve significant capex and opex savings with router-based coherent optics." DriveNets Network Cloud is being adopted by more Tier-1 operators around the world. By partnering with world-class providers like Acacia, the company continues to expand its ecosystem to support its customers' desire to mix-and-match hardware and software from multiple vendors. Learn more about DriveNets here. About DriveNets DriveNets is a leader in high-scale disaggregated networking solutions. Founded in 2015, DriveNets modernizes the way service providers, cloud providers and hyperscalers build networks, streamlining network operations, increasing network performance at scale, and improving their economic model. DriveNets' solutions – Network Cloud and Network Cloud-AI – adapt the architectural model of hyperscale cloud to telco-grade networking and support any network use case – from core-to-edge to AI networking – over a shared physical infrastructure of standard white-boxes, radically simplifying the network's operations and offering telco-scale performance and reliability with hyperscale elasticity. DriveNets' solutions are currently deployed in the world's largest networks.

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