eBook

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

We are pleased to share this independent research whitepaper by VP of Research at the Eckerson Group, Kevin Petrie. This whitepaper offers a thorough look at the transformative capabilities of the Prophecy platform, and explores how it empowers data engineering, amplifies the agility of analytics initiatives, and fosters a self-service environment for business users

Read this new research paper to learn how Prophecy is reshaping data transformation in the context of modern data architectures and includes:

  • Customer successes and use cases including cloud migration, data engineering, self-service, generative AI, and Lakehouse management
  • How the platform’s visual design, extensibility, and breadth of functionality uniquely differentiate it in the market
  • A high level architectural overview showing Prophecy seamlessly integrates into a variety of data infrastructures

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Modern enterprises build data pipelines with Prophecy