Another key consideration in a DataOps program is a unified or universal framework to manage data access and security governance across hybrid- or multi-cloud environments. The freedom and flexibility ...

One of the biggest analytics stumbling blocks for biomanufacturers is the need to prepare data in a way that makes it accessible to analytic systems and valuable to end users. Implementing a DataOps ...

Businesses have always been data-driven. The ability to gather data, analyze it, and make decisions based on it has always been a key part of success. As such, the ability to effectively manage data ...

Enterprises‌ ‌have‌ ‌struggled‌ ‌to‌ ‌collaborate‌ ‌well ‌around‌ ‌their‌ ‌data, which hinders their ability to adopt‌ ‌transformative‌ ‌applications‌ ‌like‌ ‌AI.‌ ‌ ‌The‌ ‌evolution‌ ‌of ...

DataOps, a relatively new concept, currently has a wide variety of definitions. However, the term DataOps (data operations) was first coined in 2014 by journalist Lenny Liebmann. He described DataOps ...

Agility is key to today’s enterprises responding to competitive pressures and market changes in real-time. However, most enterprises don’t have the right mix of internal processes and data-enabled ...

The industry’s use of analytics is ubiquitous and highly varied. From correlating all components in a technology ecosystem to learning from and adapting to new events as well as automating and ...

As retailers constantly adjust to shifting customer preferences, data becomes a crucial tie between the brick-and-mortar and online experience. Data is a window into the customer base, helping to ...

Data is an asset. But does enterprise treat it as such? Knowing something and doing it are two different things. Even after a business has made the transition to digital operations, data managers are ...

Every business must either become a data business or face potentially going out of business. When data goes to work, organizations can maximize productivity and profits. Data mitigates the guesswork ...