The logic in your data is the heartbeat of your organization’s reports, analytics, dashboards and applications. But that logic is often trapped in antiquated technologies that can’t take advantage of the massive scalability in the Databricks Lakehouse.
In this session BladeBridge will show how to automate the conversion of this metadata and code into Databricks PySpark and DBSQL. BladeBridge will demonstrate the flexibility of configuring for N legacy technologies to facilitate an automated path for not just a single modernization project but a factory approach for corporate wide modernization.
BladeBridge will also present how you can empirically size your migration project to determine the level of effort required.
In this session you will learn:
What BladeBridge Converter is
What BladeBridge Analyzer is
How BladeBridge configures Readers and Writers
How to size a conversion effort
How to accelerate adoption of Databricks
Connect with us:
Website: databricks.com
Facebook: facebook.com/databricksinc
Twitter: twitter.com/databricks
LinkedIn: linkedin.com/company/data...
Instagram: instagram.com/databricksinc/
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