StreamSets and Databricks Leverage DataOps to Accelerate ETL and Machine Learning 

StreamSets, a provider of a DataOps data integration platform, is partnering with Databricks, a provider of unified data analytics, to support data teams with rapid, no-code development using Apache Spark and Delta Lake.

According to the companies, the joint solution of the StreamSets DataOps Platform and Delta Lake on Databricks helps organizations apply a DataOps mentality to their critical data science and advanced analytics projects.

Specifically, the StreamSets DataOps Platform makes it easier to ingest, integrate and monitor data moving into Databricks by mitigating data drift and operationalizing the process through its full life cycle.

As a result, the Databricks customer has more operational control, greater visibility and deeper insights into data—all within a single, integrated solution. Further, given StreamSets Transformer’s Spark-native approach to data processing, even Spark non-experts can benefit from the power of Databricks.

With the combined approach, the two companies say, they are enabling more data to be delivered faster to drive analytics.

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