In the rapidly evolving data landscape, organizations seek to use data assets to drive growth and competitive advantage. The problem is, the rigid warehouse-centric data architecture makes it hard to deliver faster access to data to end users without creating data copies and siloed ETL pipelines. As cloud data lakes grow, the challenge for many organizations will be providing access to that data for exploratory BI and interactive analytics. In this video, you will learn about building a data lakehouse on Azure Data Lake Storage with product leaders from Microsoft and Dremio: - The fundamentals of a data lakehouse architecture on Azure - The need for an open data lakehouse - Unifying data access on ADLS with Dremio - A self-service experience with Dremio and Power BI See all upcoming episodes: https://www.dremio.com/gnarly-data-wa... Connect with us! Twitter: https://bit.ly/30pcpE1 LinkedIn: https://bit.ly/2PoqsDq Facebook: https://bit.ly/2BV881V Community Forum: https://bit.ly/2ELXT0W Github: https://bit.ly/3go4dcM Blog: https://bit.ly/2DgyR9B Questions?: https://bit.ly/30oi8tX Website: https://bit.ly/2XmtEnN#datalakehouse #analytics #datawarehouse #datalake #dataengineers #dataarchitects #governance #infrastructure #dremiocloud #dremiotestdrive #openlakehouse #opendatalakehouse #gnarlydatawaves #apacheiceberg #dremioarctic #datamesh #metadata #modernization #datasharing #migration #ETL #datasilos #selfservice #compliance #dataascode #branches #optimized #automates #datamovement #clustering #metrics #filtering #partitioning #tableformat #ApacheArrow #projectnessie #dremiosonar #optimization #automaticdata #scalability #enterprisedata #federated #catalogmigratortool #reflections #ML #microsoft #azure #dataarchitecture #azuredatalakestorage