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 ...

It’s no secret that companies are struggling with digital transformation. Companies know they need to innovate to win, yet 72% of executives feel they are being out-innovated by their competitors, ...

Over the past decade, the push for digital transformation has touched nearly every industry and has changed the game for BI. Now, every system and device has a digital trail, with data varying in ...

It’s sad but true, most attempts by companies to leverage data as a strategic asset fail. The challenge of both managing vast amounts of disparate data and then distributing it to those who can use it ...

STAMFORD, Conn.--(BUSINESS WIRE)--The expanding use of AI is driving enterprise interest in data operations (DataOps) to orchestrate data integration and processing and improve data quality and ...

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 ...

Digitalization requires data aggregation, standardization, and contextualization at scale. I believe the missing link to industrial transformation is a codeless solution that can aggregate, ...

Data teams within businesses and organizations strive to provide internal business users and external customers with analytical insights. But those efforts often fall short because the data and ...

The most vulnerable points in modern business operations are not where you think they are. It’s not the scale and complexity of modern data architecture that makes business operations vulnerable. It’s ...