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Here's how big data analytics techniques can pay off for organizations that are routinely storing data from many sources in many different formats.
Businesses that have been doing BI for 20 or more years say they don't have the resources to support a big data team. There's a new way around this.
DataOps is a new approach to analytics for analysts, programmers, scientists, engineers, and others. Be prepared for major cultural change.
Here are the five most common ways your organization could lose data on Kubernetes, and how to make sure it doesn't happen to you. 
We are just scratching the surface with both analytics and AI. But they are very different. Here's what those differences are—and why they matter.
Follow these top data scientists to keep up with the latest trends in the world of big data and machine learning.
To get to real governance, organizations must stop pointing fingers at IT, adopt centralized governance, and have real conversations.
Edge devices are on the rise and getting more powerful. That means data partitioning challenges are on the rise as well. Here are key considerations.
The database of the future will head off problems by being flexible enough not to lock you in. Welcome to the future: multi-model.
Hybrid cloud architectures now include edge devices that often require out-of-the-box thinking. Here are three key approaches to consider.

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