Databricks Simplifies the Path to Building Lakehouses.

Databricks have announced an accelerated path for data teams to unify data management, business intelligence (Bl) and machine learning (ML) on one platform. The new Data Ingestion Network of partners and Databricks Ingest bring data teams closer to building the new data management paradigm, lakehouse, which combines the best elements of data lakes and data warehouses, enabling Bl and ML on all of a business's data.

Historically, companies have been forced to split up their data into traditional structured data and big data, and use them separately for Bl and ML use cases. This results in siloed data in data lakes and data warehouses, slow processing, and partial results that are too delayed or too incomplete to be effectively utilized. Customers can now load data into Delta Lake, the open source technology for building reliable and fast lakehouses at scale, through the Data Ingestion Network of partners--Fivetran, Qlik, Infoworks, StreamSets, Syncsort--with built-in integrations to Databricks Ingest for automated data loading. Azure Databricks customers already benefit from native integration with Azure Data Factory to ingest data from many sources.

"Databricks powers our machine learning and business intelligence...

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