The Essential Guide to a Successful Cloud Model

| April 26, 2016

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This document will guide solution providers through the five main principles necessary to develop a practical, customized cloud transformation strategy designed to support a cloud-first customer offering. These principles include: Financial Considerations to Building a Cloud Model Marketing Approach How To “Sell” the Cloud Technical Strategy Operational Readiness

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Wise Men provides a portfolio of solutions across several Middleware platforms, Applications, Cloud, Mobility and Analytics including Big Data. Our trademarked delivery model, MicroSourcing™, provides our clients options like Goals based service, unbeatable Service Level Agreements and Pay for Performance.

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How Are You Addressing Data Privacy Compliance On-Prem?

Article | August 8, 2021

The growth of data privacy regulation around the world is changing how companies store data. But what if something that has to stay the same is your on-prem data center? This article will cover data privacy in the data center, looking at both the drivers keeping personal data on-prem, the challenges to meeting data privacy regulations in the data center, and show how NetApp Cloud Data Sense’s new support for NetApp appliances and on-prem databases can massively reduce the burden of compliance for on-prem deployments. Why Some Data Needs to Stay On-Prem Reasons for Data to Stay On-Prem Public sector guidelines Performance concerns Specific expertise on premises Barriers to migration There are a number of different reasons why companies may choose not to move data to the cloud. While these reasons are primarily due to business concerns, any personal data that is stored on-prem is going to need to stay compliant with the growing number of private data regulations in force today. Public sector guidelines Data localization can be a factor for a number of reasons. Some localities require data to be protected in redundant format, specifically using on-prem machines. There are also some regulations, such as GDPR, which limits the transfer of data out of a specific region. That can be limiting for cloud deployment, and make staying on-prem more attractive. Performance concernsThe highest performance for your data is using the machine closest to the data. In the cloud, there are high performance options available, but some companies may not want to lose the superior performance that having data and compute on the same in-house appliance provides.

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Discovering Kubernetes-Ready Solutions for Cloud Native Applications

Article | June 7, 2021

The way we architect and build applications has changed over the last decade or so. Where monoliths (or single, large codebases) used to be the standard, modern applications are now built using a combination of new architecture patterns, operational models, and software delivery services. By shifting to a microservices architecture, teams can more easily update, replace, and innovate on small, modular codebases—driving faster business innovation while reducing risk, time to market, and total cost of ownership. This modular microservices approach has spurred the use of containers as a lightweight, portable solution to the infrastructure needs garnered by these loosely coupled services. As such, containers have largely become the centerpiece of automation and DevOps in the enterprise. This gives teams the ability to capitalize on the flexibility and scalability offered by the use of containers, but it also means more moving parts and more perimeters to manage. Kubernetes has emerged as the gold standard for handling container orchestration.

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How Brands Can Effectively Utilize Social Media in Times of Crisis

Article | April 2, 2020

Social media is one of the most popular marketing channels for businesses around the world. But in this time of the COVID-19 pandemic where everything is anything but business as usual, it can be challenging for brands to know how to proceed with social media marketing. If your brand’s social content has been planned in advance, you now likely find yourself with a calendar of content that you can’t use. In the midst of a global crisis, even seemingly mundane references to things like working in an office, dining in a restaurant, taking a vacation or socializing with friends now becomes tone deaf and inappropriate.

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Top 4 Advantages of Merging Cloud Computing in Artificial Intelligence

Article | September 8, 2021

We live in the modern era of Artificial Intelligence (AI), where machines replicate human behavior. As a result, it is capable of performing many functions that are attributed to humans. According to Statista, the global AI market would reach USD 89 billion annually by 2025. The credit of the overall growth goes to the integration of cloud computing in artificial intelligence. The customized merger of these two modern technology domains has enhanced the lives of millions. In fact, in our daily life, we often use artificial intelligence when we command cloud-based digital assistants such as Siri, or Alexa, ask for directions on our phones, or get real-time traffic alerts on our GPS. Cloud Computing and Artificial Intelligence- An Overview With such an impactful collaboration, businesses are set to achieve rapid digital transformation to live up to the competitive edge. But before we ponder upon the business benefits of cloud computing and artificial intelligence integration, let us have a generic synopsis of both technologies. Cloud computing provides computing services for system resources (servers), cloud storage, databases, networking, applications, analytics, and intelligence, as and when required by the user. It assists you to share the resources, accelerate innovation, manage your infrastructure efficiently, scale with your business demands and optimize your capital expense by paying only for cloud services that you use. Artificial Intelligence, widely known as AI, is the induced virtual intelligence in machines to make them capable with intellectual powers similar to humans. The AI technology enables machines to think logically, learn from past activities, ascertain the meaning, and simplify actions. Artificial Intelligence has several applications such as text analytics, expert systems, machine language translation, speech recognition, natural language processing, sentiment analysis, and many more. How Does the Collaboration of Cloud Computing and Artificial Intelligence Help a Business? According to a study by McKinsey, across 19 different business domains and above 400 use cases, AI could create USD 3.5 trillion and USD 5.8 trillion per year in value. In addition, AI teaming up with the cloud computing environment makes organizations efficient, tactical, and insight-driven. Following are the vital four advantages of cloud computing and AI collaboration. Performs Data Mining and Analytics Cloud stores disparate data, which needs sorting and analysis to derive their hidden narratives. Artificial intelligence runs analytics to process the data, identify the pattern and determine the predictive algorithm to extract useful information. This process is known as data mining. Further, AI helps you to manage core workflows by leveraging cloud efficiency to ease out transactional processes. The integration of cloud computing with artificial intelligence supports your business in data management, determine actionable insights, deliver customer services, and augment workflows. Moreover, it equips you with accurate insights as there is no scope for human-interceded errors. Cloud Security in Real-Time Cloud Security in itself is a vast topic that engages expert’s bandwidth. However, its link with the role of AI in cloud computing recognizes its capability to detect anomalies while processing the large amount of data stored in the cloud. It can instantaneously provide an alert in real-time. Additionally, AI can also identify unauthorized attempts to access any network and helps you to block them promptly. Allows Unhindered Data Access and Improves Decision-Making Capabilities The merger of AI in cloud computing can help you avert complications related to data inaccessibility and boost your overall performance. Further, the combination helps you to mitigate potential risks in your cloud environment well in advance. As a result, it enables you to make the right decision for your business. Further, AI can facilitate seamless data transfer between on-prem and cloud environments. Maintains Cost-effectiveness and Improves Productivity The combination of cloud computing and AI intends to reduce overall costs. The merger helps you control the cost of implementing Artificial Intelligence in your business ecosystem because you don’t have to set up a separate data center. As a result, AI applications can significantly save capital expense concerning expenditure on arrangements for infrastructure. Further, it reduces the cost incurred due to manual operations and saves time to enhance your business productivity. Final Thoughts According to a recent conversation with Media 7, James Lee, Managing Director and Head of Financial Services, Analytics and Cloud Transformation at PwC, said, “A secure cloud data platform is fundamental to every successful digital transformation.” In the present competitive era, businesses are constantly looking for innovative solutions to secure their data, ensure their overall development. Cloud computing and artificial intelligence are advanced combinations to capture market attention and make a global presence. It helps you automate your processes, secure your operational data and network, control cost, boost your productivity and get accurate insights for better decision-making. Frequently Asked Questions What is the Use of AI in Cloud Computing? Businesses use AI-driven cloud computing to perform efficiently, plan effectively to extract data-driven insights. AI helps to simplify complex and redundant operations to improve productivity, perform analytics without any manual effort. Which are the Best Cloud Platforms for AI? Some of the best cloud platforms for AI are as follows: Microsoft Azure Google Cloud Machine Learning Engine Amazon ML platform services INTEL Nervana Platform Salesforce Einstein suite { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the Use of AI in Cloud Computing?", "acceptedAnswer": { "@type": "Answer", "text": "Businesses use AI-driven cloud computing to perform efficiently, plan effectively to extract data-driven insights. AI helps to simplify complex and redundant operations to improve productivity, perform analytics without any manual effort." } },{ "@type": "Question", "name": "Which are the Best Cloud Platforms for AI?", "acceptedAnswer": { "@type": "Answer", "text": "Some of the best cloud platforms for AI are as follows: Microsoft Azure Google Cloud Machine Learning Engine Amazon ML platform services INTEL Nervana Platform Salesforce Einstein suite" } }] }

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Spotlight

Wise Men Consultants

Wise Men provides a portfolio of solutions across several Middleware platforms, Applications, Cloud, Mobility and Analytics including Big Data. Our trademarked delivery model, MicroSourcing™, provides our clients options like Goals based service, unbeatable Service Level Agreements and Pay for Performance.

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