ATLANTA — The 6th International Conference on Data Science and Applications (ICDSA 2025) chose its invited speakers to s ...

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 ...

Overview MLOps extends DevOps to manage data, models, and retraining workflows that traditional software pipelines were never ...

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 ...

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 ...

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 ...

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 ...

If asked to list the top trends that are shaping the enterprise data center today, most technologists and tech investors would likely agree on a core set. The list would include technologies like such ...