Databricks announced a new suite of “GenAI Partner Accelerators” designed to simplify and accelerate data engineering and legacy system migrations for enterprises. Built by over two dozen consulting and system‑integration partners, these tools leverage generative AI to reduce manual coding and dramatically compress project timelines.
The accelerators fall into two main categories:
Data Engineering Tools: These tools automate tasks such as data ingestion, transformation, and quality checks. Engineers and analysts can use simple prompts in plain English to guide the system. Then, they can view the automatically generated code or pipelines, which include built-in data-quality checks.
Migration solutions: Designed for organizations moving from traditional ETL frameworks or on-prem data warehouses to Databricks’ Data Intelligence Platform. The accelerators analyze existing workloads, convert legacy ETL or SQL code into modern pipeline scripts, migrate schema and dependencies, and validate outputs — vastly reducing the time and effort typically required.
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These agentic tools use Agent Bricks under the hood to automatically generate SQL or Python code, build schema mappings, and produce optimized pipelines for deployment on Databricks.
Many well-known partners offer production-ready solutions. These include Cognizant, Infosys, EY, Persistent Systems, LTIMindtree, Tiger Analytics, Wipro, and others.
Databricks states that these accelerators help companies avoid slow, manual migrations. They provide a faster, scalable path. By automating essential tasks like code conversion, quality assurance, and pipeline deployment, organizations speed up their time-to-value. This also frees engineering teams to focus on strategic work.
In a landscape where modern analytics, AI and data workloads demand speed, scalability and reliability, Databricks’ partner ecosystem now gives enterprises a practical toolkit — bridging legacy and modern systems while embedding AI-driven intelligence throughout their data lifecycle.