Analytics

API Analytics and Monetization with Choreo and Moesif

We're excited to announce the partnership between Choreo and Moesif, bringing you an integration for improved API analytics and monetization. Choreo is our application development suite designed to accelerate the creation of digital experiences. It simplifies the process of building, deploying, and monitoring cloud-native applications, boosting productivity and fostering innovation in organizations.

Yellowfin 9.9 Release Highlights

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.

Let Real-Time Data Visualization Drive Your Storytelling

Stories are the crux of effective communication. According to a Stanford University study, nearly two-thirds of people remember a story that’s part of a presentation. The study also found that speakers who merely present facts and figures only achieve a 5% recall rate among their audience. When your customers deliver analytics and reporting, the data visualization experience should be a memorable one.

Comparing Data Visualizations: Bar vs. Stacked, Icons vs. Shapes, and Line vs. Area

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.

From Hive Tables to Iceberg Tables: Hassle-Free

For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. But as the data volumes, data variety, and data usage grows, users face many challenges when using Hive tables because of its antiquated directory-based table format. Some of the common issues include constrained schema evolution, static partitioning of data, and long planning time because of S3 directory listings.