All things data operations in the machine learning age
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DataOps Report Breakdown: DataOps Outlook

The chart above examines which functional areas within an organization plan to hire in DataOps. Unsurprisingly, 79% of those respondents in IT said they will hire in DataOps. The majority of Data Science, Engineering, and Analytics respondents also have plans to hire, which should come as no surprise.

What is surprising however, is that 53% of those who work in other functions also have plans to hire in DataOps. This “Other” category includes Product Management, Marketing, and even areas like Finance. This suggests business owners in almost all functional areas have the need to integrate, process, and derive value from data.

The Definitive Data Operations Report 2017

At Nexla, we are constantly thinking about the challenges of data operations for cross-company data. We’ve spoken with hundreds of companies about the unique effort required to send and receive data across company lines. But few benchmarks exist in the market for companies looking to learn from best practices. We decided to investigate.

This first-of-its-kind survey asked over 300 respondents about how they derive value from data. We surveyed data professionals from 40 different industries, with tenures ranging from two years to more than ten. In this post, we summarize some of the key benchmarks that emerged from the study. You can read the full report here, and a brief summary in this post.

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