Systems | Development | Analytics | API | Testing

Analytics

Why do we need DataOps Observability?

DevOps was started more than a decade ago as a movement, not a product or solution category. DevOps offered us a way of collaborating between development and operations teams, using automation and optimization practices to continually accelerate the release of code, measure everything, lower costs, and improve the quality of application delivery to meet customer needs.

ThoughtSpot and Databricks make governed, self-service analytics a reality with new Unity Catalog integration

Two years ago, we announced our Databricks partnership—including the launch of ThoughtSpot for Databricks, which gives joint customers the ability to run ThoughtSpot search queries directly on the Databricks Lakehouse without the need to move any data. Since then, we’ve empowered teams at companies like Johnson & Johnson, NASDAQ, and Flyr to safely self-serve business-critical insights on governed and reliable data.

Talend in 2023: Customer-focused, customer-forward

Prepping for a sales kick-off puts the focus on an organization’s customers unlike any other event. There is no selling — or success — without understanding and fulfilling the needs of our prospects and customers. As our gathering in Nashville last month proved, Talend is laser-focused on meeting customers wherever they are in their data journey, with everything they need to solve their most pressing data management challenges.

Data Talks Helps Sports Brands Score More Sales with Snowflake's Data Cloud

Data Talks fills a gap in the sports market by giving brands the data they need to truly understand their customers. But when your platform is responsible for continued ticket, merchandise, and sponsorship revenue, it needs to deliver insights fast. Here’s how Data Talks delivers data quickly with a rapid insights platform powered by Snowflake. From football fans filling out stadiums to baseball followers streaming every game, few customers are as avid and loyal as sports fans.

An Overview of Streaming Analytics in AWS for Logging Applications

Streaming analytics in AWS gives enterprises the ability to process and analyze log data in real time, enabling use cases that range from delivering personalized customer experiences to anomaly and fraud detection, application troubleshooting, and user behavior analysis. In the past, real-time log analytics solutions could process just a few thousand records per second and it would still take minutes or hours to process the data and get answers.