Streaming Pipelines to Data Warehouses - Use Case Implementation

Data pipelines do much of the heavy lifting in organizations for integrating, transforming, and preparing data for subsequent use in data warehouses for analytical use cases. Despite being critical to the data value stream, data pipelines fundamentally haven’t evolved in the last few decades. These legacy pipelines are holding organizations back from really getting value out of their data as real-time streaming becomes essential.

This whitepaper covers how to implement a solution for connecting, processing, and governing data streams for data warehouses. You'll learn about:

• Sourcing from data warehouses (including use of Change Data Capture)
• Sinking to data warehouses
• Transforming data in flight with stream processing
• Implementing use cases including migrating source and target systems, stream enrichment, outbox pattern, and more
• Incorporating Security and Data Privacy, Data Governance, Performance and Scalability, and Monitoring & Reliability
• Getting assistance where needed

Download the whitepaper today to get started with building streaming data pipelines for your data warehouse (Snowflake, Databricks, Amazon Redshift, Azure Synapse, Google BigQuery, Teradata, Cloudera, and more).