By Sean Knapp, Founder and CEO, Ascend

Data Centricity Will Change People and Processes in 2020 and Beyond

Data has become the center of business operations and it's shaping roles and responsibilities in new ways. This will only accelerate in 2020 and beyond. Below are a few specific examples of how I see these changes playing out.

2020 Will Be the Year of the Citizen Data Engineer

2019 was the year of the citizen data scientist-- individuals who utilize data science practices and tools but whose training and primary role is not that of a data scientist. 

The explosion in data science initiatives across departments and job functions has stirred an increasing need for streamlined and scalable access to data, a function typically handled by data engineers. Now, with an ever increasing demand for data engineers, we expect to see a steep increase in compensation for skilled data engineers as data pipelines become more critical across the enterprise. But that won't be enough to supply data engineers in the numbers needed. To fill the gap, I predict 2020 will be the year of the citizen data engineer, where those outside of the data engineering team will oversee and manage data pipelines and the overall data lifecycle. Many organizations have already begun to identify and train employees within their company as a way to manage the dearth of data engineers, creating a growth opportunity for those interested in the field, and we anticipate this trend to continue over the next year.

DataOps Will Reign in the 2020s

With an increasing number of systems, use cases, and the sheer volume of data, data pipelines will be top of mind for organizations in 2020 and beyond. Businesses will continue to pursue more advanced data, analytics, and AI initiatives across their organization, which will necessitate DataOps sophistication to keep pace with the accelerating data development lifecycle. DataOps is by no means a new term or methodology, but increasingly, businesses will begin adopting DataOps practices to be able to scale and deliver on their investments in data, analytics and machine learning applications. 

The Fate of AI Depends on AI

The 2010s closed out with an AI frenzy - with marketing hype and spending around the technology at an all time high. While organizations worldwide are anticipated to spend more than $1.8 trillion annually by 2021 on big data and AI-driven digital transformation efforts, many will struggle to translate those investments into business success. This is due to insufficient resources and expertise to support data initiatives, difficulty accessing siloed data, and an increased urgency for fast analysis and delivery. We've seen this type of technology gold rush before, and unless we address the core issues at hand, we will be doomed to fail. 

The fate of AI will depend on AI itself, or rather the ability to utilize automation to ensure successful AI and big data projects. I expect to see that advancements in automated data and delivery systems in the coming decade will help businesses increase their success rates in these AI and big data initiatives across industries. 

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