Systems | Development | Analytics | API | Testing

Analytics

Database Table Source in Astera Data Stack

In this video, we will see how a Database Table Source object works in Astera. The Database Table Source object is used to retrieve data from a database table. It offers incremental reads via change data capture, supports multi-way partitioning for enhanced performance, and allows customization with WHERE clauses and sorting options.

Data Observability + FinOps for Snowflake Engineers

Snowflake data engineers are under enormous pressure to deliver results. This data sheet provides more context about the challenges data engineers face and how Unravel helps them address these challenges. Specifically, it discusses: With Unravel, Snowflake data engineers can speed data pipeline development and analytics initiatives with granular and real-time cost visibility, predictive, predictive spend forecasting, and performance insights for their data cloud.

Yellowfin BI Celebrates 20 Years of Embedded Analytics Innovation

AUSTIN, TEXAS, USA, January 25, 2024 - Yellowfin, a leading global provider of business intelligence (BI) and data analytics software, is proud to celebrate 20 years of innovation in the business intelligence (BI) and data analytics industry. Founded in 2004 with a mission to make data accessible and actionable for everyone, Yellowfin has grown into a global force, empowering businesses of all sizes to unlock the power of data and gain a competitive edge.

Top 3 Healthcare and Life Sciences Data + AI Predictions for 2024

This year may be the most innovative on record. Recent advances in AI are beginning to transform how we live and work. And the potential impacts of artificial intelligence (AI) on the healthcare and life sciences industries are expected to be far-reaching. It’s essential for organizations to leverage vast amounts of structured and unstructured data for effective generative AI (gen AI) solutions that deliver a clear return on investment.

Snowflake + Unravel: A Dynamic Duo to Supercharge Speed and Efficiency

GenAI and analytics are increasing demands on data teams. They need new ways to accurately forecast data cloud spend, improve efficiency, and increase automation. Organizations are increasingly turning to purpose-built AI to enable data observability and FinOps that dramatically accelerates time to launch new data products, increases spend predictability, and minimizes cloud waste.

From Reporting to Decision Science: Inside HP with Juergen

You’ve heard the term data science, but have you heard about decision science? Juergen Kallinger, VP of Data and Insights at HP, shares valuable insights and reflections from his 22-year journey at HP. In this episode, Juergen dives into HP’s pivotal shift from solely reporting, to the dynamic realm of decision science and how it’s aligned their data team.

Confluent's Customer Zero: Building a Real-Time Alerting System With Confluent Cloud and Slack

We talk a lot about how customers can use Confluent as the data backbone for event streaming applications and enable a new class of event-driven microservices by completely decoupling services from one another. With Confluent, organizations can rapidly build and deploy business applications with greater flexibility, support larger scale, and be more responsive to customer demands. But we don’t just talk about it, we do it ourselves as Confluent’s “Customer Zero”!

How To Build Scalable and Resilient Microservices | Microservices 101

Building scalable and resilient microservices requires an approach that eliminates the need to treat them as special. They should be treated as easily replaceable building blocks. This means eliminating bottlenecks and single points of failure but it can also mean changing from a pull-based approach to a push-based approach. CHAPTERS.