Systems | Development | Analytics | API | Testing

How to preprocess data using BigQuery ML so you can get better insights and models.

In the realm of big data analytics, Hive has been a trusted companion for summarizing, querying, and analyzing huge and disparate datasets. But let’s face it, navigating the world of any SQL engine is a daunting task, and Hive is no exception. As a Hive user, you will find yourself wanting to go beyond surface-level analysis, and deep dive into the intricacies of how a Hive query is executed.

Great data visualizations have the power to persuade decision makers to take immediate, appropriate action. When done well, data visualizations help users intuitively grasp data at a glance and provide more meaningful views of information in context. Good data visuals give busy workers a high-level summary of important data. They also offer a big-picture perspective and highlight trends, anomalies, and outliers while giving users the option to drill down into details and ask new questions when needed.

Throughout the One Big Cluster Stuck series we’ve explored impactful best practices to gain control of your Cloudera Data platform (CDP) environment and significantly improve its health and performance. We’ve shared code, dashboards, and tools to help you on your health improvement journey. We’d like to provide one last tool.

With updates to our installer user interface (UI), advanced functions, filters and more, Yellowfin 9.9 is a must-have update to streamline and improve your analytics experience. The latest release brings a fresh look for the Yellowfin installer to make it easier to install and upgrade Yellowfin, along with additional enhancements added for existing parts of the suite, including new Custom Advanced Functions, predefined filters and Bookmarks.