Building Next-Gen Data Pipelines with Databricks Delta

Organizations that operate worldwide typically need to manage data both locally and globally. Local business units and subsidiaries must address region-specific data and accounting standards, regulations, customer requirements, and market drivers. At the same time, corporate headquarters must share data broadly and maintain a complete view of performance for the entire enterprise. For many global firms, data is the business. They need state-of-the-art data management just to remain innovative and competitive. Hence, multinational businesses face a long list of new business and technical requirements for modern data management.

As more companies are leveraging the Data Lake to run their warehouse workloads, we’re seeing many companies move to an Open Data Lakehouse stack. The Open Data Lakehouse brings the reliability and performance of the Data Warehouse together with the flexibility and simplicity of the Data Lake, enabling data warehouse workloads to run on the data lake.

In this 50-minute overview and product demo, Founder and CTO, Thomas Bolt, will show you how you get a strategic and automated concept for quality assurance in your data-driven development project. You’ll learn why hundreds of data analytics projects fail with too less or inadequate testing and how to implement a strong testing concept easily by using BiG EVAL's test automation software for data-driven projects.

TDWI research has found that organizations are increasingly modernizing their data warehouse environments. Often the current environment is not sufficient to support new analytics initiatives or they need to support new data types for analytics. Many enterprises are moving to the cloud as part of this journey. In fact, cloud data warehouses and cloud data lakes are already mainstream. The popularity of automated tools is growing as environments become more complex.