Ashish Thusoo and Joydeep Sen Sarma know a thing or two about big data. They led the team that built Facebook's data infrastructure, and they are also the co-authors of the Apache Hive project and ...

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the ...

DataOps is a viable approach that combines data engineering into operations processes. It aims to promote data management practices and procedures that improve the speed and accuracy of analytics.

As organizations continue their digital transformation, the demand for timely, consumption-ready data has never been higher. Yet simply adopting data operations tools is not enough to improve data ...

Enterprises‌ ‌have‌ ‌struggled‌ ‌to‌ ‌collaborate‌ ‌well ‌around‌ ‌their‌ ‌data, which hinders their ability to adopt‌ ‌transformative‌ ‌applications‌ ‌like‌ ‌AI.‌ ‌ ‌The‌ ‌evolution‌ ‌of ...

DataOps, an adaptation of what’s traditionally known as DevOps, has evolved into an essential component of modern business operations. DataOps applies the concepts that have fostered more agility and ...

As industrial organizations scale digital transformation initiatives, the ability to reliably move, contextualize, and standardize operational data is critical. Without the right data architecture, ...

Because building reliable data pipelines is hard, and the first step to becoming a data-driven organization is trusting your data. It’s 8 a.m., and a business leader is looking at a financial ...

Back in 2006, British mathematician Clive Humby stated that data was the new oil. Like oil, data isn’t useful in its raw state and must be refined, processed, and distributed to deliver value. Nearly ...