Financial dashboards bring performance into focus by collecting the most important metrics and indicators in one location. But when organizations build their financial dashboards from the ground up, challenges often arise. A primary hurdle is making the right design choices to create dashboards that drive successful business decisions. To overcome this hurdle, it helps to incorporate ideas that have already been implemented, evaluated, and improved on by others.

At Snowflake Summit 2022, we introduced a new way of building apps with the Snowflake Native App Framework. Today, we are excited to bring the power of the Snowflake Native App Framework to developers around the world with the public preview in AWS. Developers can now start building and testing Snowflake Native Apps in their accounts in AWS. Distribution and monetization capabilities will be available in public preview on AWS later this year.

Available in beta, we have introduced new version control REST APIs for Git integration in the 9.3.0.cl release of ThoughtSpot Analytics Cloud. ThoughtSpot administrators can now link their instances to a GitHub repository and utilize continuous integration and deployment (CI/CD) best practices to effectively manage their organization's analytic content throughout its lifecycle.

At ThoughtSpot, we know how important it is for businesses of every size and industry to empower every knowledge worker with personalized, actionable data-driven insights. These insights are your secret sauce to making better business decisions, growing faster, and delivering customer experiences that keep people coming back for more. But how do you scale self-service analytics to business users without completely overwhelming your data teams?

You may already be familiar with dbt, but just to be sure we're on the same page, let's revisit the concepts. The Data Build Tool (dbt) is a widely used framework provided by dbt Labs, specifically designed to bridge the gap between data analysts, data engineers, and software engineers, resulting in the creation of a new role in data and analytics: the analytics engineer.

Over time, using the wrong tool for the job can wreak havoc on environmental health. Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster.

With any new, transformative technology comes a fear of the unknown, as I explored in my first blog of a new series on generative AI. Companies are pulled between acting quickly to avoid being left behind and proceeding with caution to avoid major missteps.

Over the past few years, software vendors moved their applications to the cloud. Microsoft committed heavily to the cloud across all its product lines, including the Dynamics family of ERP and CRM solutions. That will mean an eventual migration to the cloud for customers of Microsoft Dynamics AX, Microsoft Dynamics CRM, and the legacy Microsoft GP, SL, and NAV products.

In this blog, the team at Yellowfin Japan demonstrates how to take advantage of Yellowfin's data visualization capability in the form of Box and Whisker charts, using the example of analyzing the percentage of foreign population prefectures. So, what is a Box and Whisker Chart, and what does it look like in Yellowfin? Blog Contents hide Box and Whisker Chart Overview and Analysis Examples What is a Box and Whisker Chart?