Businesses and federal agencies today are facing a mammoth digital challenge: they’re striving to find ways to extract value from data. That is, they want to achieve specific business outcomes while the volume and variety of available data are rapidly increasing.
To solve this challenge, organizations are replacing traditional data management with an emerging set of practices focused on collaboration and automation. It’s called data operations, or DataOps, a confluence of advanced data governance and analytics delivery practices that encompasses the entire data life cycle, from data retrieval and preparation to analysis and reporting. DataOps promises to help organizations optimize their data management; drive initiatives involving data-intensive technologies such as artificial intelligence (AI), machine learning (ML), and deep learning (DL); and consistently produce desired outcomes.
Download MIT Technology Review’s insights regarding DataOps history, culture, and best-practices to discover your DataOps Advantage.