Welcome back to the 2017 Definitive Data Operations Report MiniSeries! This week, we’re covering key data activities in DataOps as data continues to grow and how it affects the need for hiring as well as tools for hiring.
Wait, what are they doing? Data Activities.
Every day, data professionals and executives are spending most of their time on analysis. On average, 22% of respondents spend time on analysis with some respondents reporting they spend 100% of their time on analyzing data–this is no surprise. However, when looking at the overall picture of key DataOps activities, integration, troubleshooting, data pipelines, and ETL jobs combined take up almost half of respondent’s time.
These tasks are central and crucial to maintaining data operations efficiently in this time of data growth. The more time data pros and executives need to spend on DataOps tasks, the less time is spent on data analysis in order to derive value.
Fast & Furious: Data Growth
In fact, 63% of respondents reported their data is growing at least 100 Gigabytes per day with 13% of respondents reporting their data is growing at least 1 terabyte a day. One terabyte can hold 33 copies of the entire Star Wars saga. Calculated over a month, that’s almost eight thousand movies!
Sharing is caring
With data growing so quickly, it is important to find efficient ways to ingest and share data. Surprisingly, the most popular tools currently used to share data are FTP (37%) and Dropbox (16%). Given how long these tools have been around, it will be interesting to see how much longer these formats remain the most popular.
Open Source in the Age of SaaS: What the Fivetran-DBT Merger Means for dbt Core
The Fivetran–dbt merger tests the future of open source in a SaaS-dominated world. Can dbt Core stay community-driven as corporate incentives reshape the modern data stack? Here’s what’s at stake—and what comes next.
Poor data management can cost organizations 15–20% of revenue. Reusable, scalable data products help—but only if they’re consistent and reliable. A Common Data Model (CDM) standardizes and structures data, ensuring accuracy, scalability, and long-term value.
Fivetran and Nexla are leading data integration platforms, but they take different approaches. Learn how they compare on features, deployment, and governance to find the right fit for your data strategy.