Cloud is a pathway to innovation. Where yesterday’s cloud deployments were about moving an on-premises infrastructure in your data center to a cloud environment, companies today are using cloud platforms to build new features for their products and services that are integrated at a software level.
Artificial intelligence, machine learning, and big data capabilities are no longer nice to haves—they’re an essential part of an enterprise’s growth strategy. Cloud makes it easier and more cost-effective to leverage such technologies.
As if the need for more advanced skills wasn’t enough, the tendency for a multi-cloud approach means that teams will need to know how to use services from multiple platforms—chief among them AWS, Microsoft Azure, and Google Cloud Platform—to stay competitive. As always, for any new services that you adopt, strong security practices—and the skills to implement them—must be part of the process.
For companies looking to incorporate big data, AI, and machine learning into enterprise applications, here are some of the top cloud skills in demand that your teams will need to learn to stay competitive.
Data is among an organization’s most important assets. The cloud helps companies leverage a variety of tools for processing, analyzing, and managing high-volume, diverse data sets without the time or capital investment required for an on-premises deployment.
AWS, Azure, and Google all have big data services for analysis, visualization, processing, and administration, and they are continuing to add new features and services to reduce complexity and time to value.
As companies ramp up their big data processing efforts, they will likely have two issues. First, building a scalable big data analytics infrastructure is time-consuming and expensive. Second, many people with data analytics backgrounds are used to writing queries in SQL, but most big data processing systems are based on Hadoop MapReduce and similar frameworks, which makes writing queries more