According to IDG, when customers consider updating to the latest release of a product, they expect new features, enhanced security, and better performance, but increasingly want a more streamlined upgrade process. With each new release of CDP Private Cloud, this is exactly what we strive to deliver. Along with a host of new features and capabilities, we are improving the upgrade process to be as painless as possible.

Understandably, however, the many automation, AI and machine learning technologies that come with modern analytics solutions can sometimes be hard to keep up with. One area we get asked a lot about is ABM, which we offer with Yellowfin Signals, and what exact advantages it brings to the table for everyday analysis and insight generation.

The exponential adoption of IT technologies over the past several decades has had a profound impact on organizations of all sizes. Whether it is a small, medium, or large enterprise, the need to create web applications while managing an extensive set of data effectively is high on every CIO’s priority list. As a result, there has been an ongoing effort to implement better approaches to software development, data analysis, and data management.

Companies deploying big data analytics to gain competitive advantage can quickly sour their successes by lacking a big data governance strategy. Which turns their data assets into data liabilities. In this article, we dive into the field of information governance and information management and explore how to set up and automate a big data governance program for success. Big data governance is a set of processes and principles that ensure the high value of data throughout its lifecycle.

As a developer, you're no stranger to your vast and varied data environment… Or are you? The tremendous amount of data your organization collects is stored in various sources and formats. You need a way to understand where and what data is, to be able to do what you need to do: build amazing event-driven applications.

Heroku is a powerful platform for application development. Users can build and deploy on the cloud, and you can effortlessly scale up once your app takes off. And behind every app, you'll find an equally powerful database: Heroku Postgres. If you're building Heroku apps, you'll find them to be a rich source of operational and customer data. Add in the right Business Intelligence (BI) tools, and you'll be able to derive insights about the inner workings of your organization.

Cloudera Data Engineering is a serverless service for Cloudera Data Platform (CDP) that allows you to submit jobs to auto-scaling virtual clusters. CDE enables you to spend more time on your applications, and less time on infrastructure. CDE allows you to create, manage, and schedule Apache Spark jobs without the overhead of creating and maintaining Spark clusters.

The blog “Migrating Apache NiFi Flows from HDF to CFM with Zero Downtime” detailed how many common NiFi dataflows can be easily migrated when the Hortonworks DataFlow and Cloudera Flow Management clusters are running side-by-side. But what if you lack the resources to run multiple NiFi clusters concurrently? Not a problem.