The low-code lakehouse architecture guide
Empower any data user at any skill level to harness the potential of Databricks and modernize your process for developing, deploying, and managing data pipelines.
The popularity of data lakehouse architecture is increasing for good reason, but traditional data engineering can be complex, time-consuming, and costly. The solution is Prophecy, which enables any data practitioner to build out complex pipelines at scale, quickly and easily.
This architecture guide will show you how to achieve a modern, low-code data lakehouse architecture powered by Databricks and Prophecy that includes:
- a rich drag-and-drop visual interface
- built-in data transformation and enrichment
- component reuse and sharing
- automatic generation of high-quality Apache Spark code
- and support for both batch and streaming workloads
Say goodbye to the headaches of traditional data engineering and hello to a more efficient and effective way of working with data.
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
Get the guide