Low-Code Apache Spark™
and Delta Lake
A guide to making data lakehouse even easier
The ETL/computational engine Apache Spark makes data engineering efficient and scalable. And Delta Lake, an underlying storage format, delivers data warehouse-like simplicity along with advanced update operations and ACID guarantees. Data Lakehouse unifies both of these into a single layer that has a flexible data preparation space combined with a structured and governed space.
Even though Spark and Delta are the perfect basis for your future data pipeline, and the Data Lakehouse architecture allows us to enable a tremendous amount of new use cases, the usability and productivity still remain a challenge.
In this eBook, you’ll learn how low-code for lakehouse can enable data engineers to:
- Visually build and tune data pipelines into well-engineered Spark or PySpark code
- Directly store code in Git while leveraging testing and CI/CD best practices
- Collaborate on multiple data pipelines within each level of data quality
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