Key Data Technology Skills for 2020
Data technology is rapidly evolving and learning some new skills can keep you evolving along with it. Here are some of the key data technology skills that are ‘hot’ in 2020. Just to keep things real, I’ll talk a little about why I think some of it may not necessarily be what it’s all cracked up to be.
Data scientists continue to be in high demand, as companies look to get the most value from their data. For data scientist, programming skills are needed - like Python, Perl, C/C++, SQL, and Java. For tools, some of the key ones would be SAS, Hadoop, Spark, Hive, Pig, and R. Data scientists also should have the ability to understand and manage data that is coming in unstructured form from different channels.
Big Data is both structured and unstructured data at high volume, with variety of types, and with high velocity. Some of the Big Data technologies that you need to gain considerable expertise in are Apache Hadoop, Spark, SQL, NoSQL, using statistical and quantitative analysis models, data visualization, and an ability to write computer programs in R, Java, Python, and Scala.
In 2020, one-third of all data will pass through the cloud. Having an in-depth knowledge of Linux, virtualization, storage, networking, security, disaster recovery, web services, APIs, devops, and programming languages SQL, Python and Java can help you take on the challenging role of a Cloud Computing professional in today’s world. Knowledge of at least one or more of the major cloud platforms AWS, GCP and Azure is required for roles in cloud computing.
AI is a broad concept, where machines are designed to carry out a specific set of tasks in a smart way. Artificial Intelligence Engineers take business automation to the next level; they directly deal with the optimization of business operations and practices. Most careers in AI require coursework and experience in a variety of math and science-related topics. The top skills needed for career in AI are Machine Learning and Data Science, and some key programming languages for AI are Python, R and Java.
BI professionals need to understand the technical nuances of setting up and running a system, make sense of the business viewpoint, and convert the business queries into analytical know-how for rapid realization of business solutions. The top skills needed for BI are data analysis, problem-solving, specific industry knowledge, communication skills, and business acumen. Some technical skills would include SQL, data warehousing, data visualization, ETL, data modeling and some programming. Knowledge of one or more reporting software is required for success in business intelligence.
Why it’s not all that it is cracked up to be? Well, it is mostly because companies and organizations don’t really know what to do with a lot of it. Often, it is not aligned with the corporate mission, or if it happens to be, it still doesn’t align well because few people know how to align it correctly. We have seen this numerous times, and the result is that often the politics then get in the way of progress. The optimal value is hardly ever achieved.
We recommend you read about us and what we do for Digital Transformations to get the most out of your investments in top talent and skills that you are bringing in or have brought in to your organization. https://www.ibisviz.com/digital-transformation