Systems | Development | Analytics | API | Testing

Many of you rely on Dataflow to build and operate mission critical streaming analytics pipelines. A key goal for us, the Dataflow team, is to make the technology work for users rather than the other way around. Autotuning, as a fundamental value proposition Dataflow offers, is a key part of making that goal a reality - it helps you focus on your use cases by eliminating the cost and burden of having to constantly tune and re-tune your applications as circumstances change.

Since the release of Cloudera Data Visualization (DV) back in Oct 2020, our primary mission has been to expand access to data analytics and predictive insights across enterprise businesses.

With summer just around the corner, things are really heating up. But you’re in luck because this month BigQuery is supplying a cooler full of ice cold refreshments with this release of user-friendly SQL capabilities. We are pleased to announce three categories of BigQuery user-friendly SQL launches: Powerful Analytics Features, Flexible Schema Handling, and New Geospatial Tools.

With billions of industrial IoT (IIOT) devices in place, generating massive volumes of data from “the edge,” the potential for proof of concept success for use cases in the factory can be paralyzing. While the value of this digital revolution, aka Industry 4.0, is clear, realizing the full promise has been slow. Research and real-life experience from Accenture shows that many manufacturers get stuck early on or can’t get beyond proof-of-concept pilots to scale.

The move into any new technology requires planning and coordinated effort to ensure a successful transition. This blog will describe the four paths to move from a legacy platform such as Cloudera CDH or HDP into CDP Public Cloud or CDP Private Cloud. The four paths are In-place Upgrade, Side-car Migration, Rolling Side-car Migration, and Migrate to Public Cloud.