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TDWI Upside - Where Data Means Business

Data Lakes and Data Storage


The Evolution of Data Lake Architectures

For data lakes, as with any valuable enterprise data set, architecture is a requirement. But it is also a moving target, due to ongoing evolution.

Keep Privacy and Governance in Mind When Developing or Updating Your Systems

Enterprises face conflicting and complex privacy and governance regulations that don’t make it easy to comply. These tips can help you get a handle on compliance.

I Have a Data Warehouse, Do I Need a Data Lake Too?

When building your data and analytics program, you must decide whether you need a data warehouse, a data lake, or both. Understanding the difference is the first step.

Defining the Hybrid Data Warehouse

Data warehouse architecture continues to evolve as users modernize their warehouses and as vendor, open source, and cloud provider communities roll out innovative new platforms.

Welcome to the Lakehouse

A new decade, a new phrase to conjure with. The "lakehouse" is generating some interest and debate, but it needs to prove itself as an architecture.

A Case for Managing Data Uniquely for Each Form of Advanced Analytics

From mining to machine learning, each form of advanced analytics has its own requirements for how data must be managed. Failing to satisfy these requirements leads to hamstrung analytics.

Proactive Prevention of Five Common Causes of Data Loss

How to prevent and quickly remedy five of the leading causes of data loss in your enterprise.

Why Enterprises Should Take a Layered Approach to Their Data Strategy

H.Y. Li of Alluxio explains why the layers of your data platform are an essential part of your data strategy.

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