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 ...

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 ...

DevOps teams are rapidly adopting agentic AI to automate coding, infrastructure, and operations, shifting engineers into supervisory roles. Analysts warn that scaling these systems hinges on ...

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 ...

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 ...

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 ...

DevOps has proven to be an effective means of reshaping IT and developer organizational culture and processes in ways that improve software quality, release cycles and deployment robustness. As I ...

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 ...

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, ...