What’s DataOps?

DataOps data transformations

 

Define: DataOps

da·ta·ops
/ˈdadə,ˈdādə·äps/
noun

Inspired by the DevOps movement, Data Operations controls the flow of data from source to value, speeding up the process of deriving value from data. DataOps platforms turn ad-hoc engineering work into a scalable, repeatable process. Whether it is integrating with data sources, performing transformations, converting formats, and writing or delivering data to its required destination, DataOps takes care of the grunt work so data can be analyzed, modeled, or surfaced for end users. DataOps also encompasses the monitoring and governance of data flows, while ensuring security and scale.

DataOps is a rapidly growing field. 70% of companies surveyed has plans to hire in the DataOps function within the next year, regardless of company size or industry. DataOps is no longer a tech trend, but a business trend.

91% of companies are currently using or have plans to use third party data, making inter-company data collaboration a norm. However, many companies across the board continue to face challenges in driving insights from their data. 88% of professionals cite data access as their biggest challenges, while 46% cite data science/analytics skillsets to be a challenge.

Overall, any data professional or executive faces the overarching problem of lack of support coupled with streamlining challenges. With DataOps as a growing field, there is still a lot to discover and understand before it can work like a well-oiled machine. Data Operations will quickly become the backbone to much of any company’s data work, and it’s time to change the way we approach DataOps.

The DataOps revolution is here. We now know that company-to-company data transfer is only going to grow. Companies would be wise to put the processes and tools in place now to prevent data heartache down the road. It’s not an easy feat, but Nexla is here to help.

Nexla automates your DataOps with minimal engineering so you can quickly derive value from your data. We scale your data operations infrastructure, so you can scale your business.