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Trends in 2018: SQL, BI, and Data Science

March 2018- by Evan Pate, Contractor Retention & Replacement Advocate at Apex Systems

trends 2018 sql data science bi

A big question for people who are both starting their career and have a wealth of experience is “What is next? What technologies are growing? What should I invest my time into learning and developing?” These are questions that can have constantly evolving answers and are sometimes the most difficult to predict. Looking through blogs, trends, and different aggregators, we have compiled some trends information below. For the most part, this covers the areas of data management, science, and databases that are expected to increase in popularity/adoption in 2018.

Three Key Skills “In Demand”

  1. SQL- One of the biggest questions Apex gets is “what skills do I need to develop to be more marketable to companies?” Using insights from an analytics tool we have that pulls information from all job postings published nationally and the Department of Labor Statistics, we found that SQL is a top 5 need/requirement for Database Developers, Business Intelligence, and Data Science. This is in large part due to the increase in Machine Learning, Cloud Growth, and Data Humanism.
  2. Python overtaking R- For multiple years, the most popular language for Big Data has been trending towards Python. Python was not created specifically for data analysis, but due to its dynamic typing, easy to learn syntax, and ever-increasing base of libraries, it is now an ideal candidate for developers to start delving into data science. However, R will remain the go to language for particularly data-heavy programming.
  3. Data Science – There are multiple areas that are expecting considerable growth in the Data Science field.
    • Artificial Intelligence: According to a study by Gartner Analytics, 59% of enterprise organizations are still building AI strategies, while the remaining 41% have already adopted some form of AI logistical and statistical systems.
    • Intelligent Apps and Analytics: As the field of AI continues to gain momentum, the need for intelligent apps and analytics will also rise. Virtually every app, application, and service will incorporate some level of AI.
    • Cloud to the Edge: Edge computing describes a computing topology, where information processing, content, and delivery are placed closer to the source of the information. Specifically used to create service–oriented models and centralized control. – is there supposed to be something else in this statement? Is it supposed to be combined (with transition) with this next sentence? Aids with coordination structure with edge mostly being used as a delivery style.

While this list doesn’t cover every trend to watch out for, it provides guidance on where technology will be heading this year.

Want more specific trends information around your skill set, target career path, specific geography, etc.? You can reach out to Evan Pate, including specific questions/data requests, via