Overcoming DevOps obstacles—such as slow, manual, poor-quality test data—is key toward accelerating pipelines. With speed being a central success factor for DevOps pipelines, increasing velocity ...

Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key Data scientists have some practices and needs in ...

Last week’s Informatica World 2016 brought out a lot of talk involving data quality, real-time live data and the automation of ingesting and analyzing data in order to turn it into something ...

DevOps adoption can invite a wealth of opportunities for application development, yet data management continues to lack the speed, interoperability, and flexibility that prevents a successful DevOps ...

You often hear that data is the new oil. This valuable, ever-changing commodity has begun to play a starring role in many cloud-native applications. Yet, according to a number of DevOps teams, data ...

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 ...

It may be a stretch to call data science commonplace, but the question “what’s next” is often heard with regard to analytics. And then the conversation often turns straight to Artificial Intelligence ...

Data science and machine learning are often associated with mathematics, statistics, algorithms and data wrangling. While these skills are core to the success of implementing machine learning in an ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Data governance is an umbrella term encompassing several different disciplines and practices, and the priorities often depend on who is driving the effort. Chief data officers, privacy officers, ...