Shift Left: Unifying Operations and Analytics With Data Products
Key Takeaways
⇨ High-quality business data is essential, necessitating the prevention and mitigation of bad data across the entire organization.
⇨ Shifting data processing and governance left improves control over source data models and reduces duplicate pipelines, thereby enhancing data quality from the outset.
⇨ The ebook explores challenges with current data pipeline approaches and introduces strategies for building headless data architectures using technologies like Apache Flink® SQL and Apache Iceberg®.
The need for high-quality business data is greater than ever, so preventing and mitigating bad data—across the entire business—has become a critical capability. Extract-transform-load (ETL) and extract-load-transform (ELT) data pipelines have long been the primary means for getting data into the analytics plane. But data consumers in the analytics domain have had little to no...
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