Semantic Layer and Data Lakehouse to Scale Analytics for Everyone

April 15, 2022

Happening on Thursday, April 21, 2022 11:00 AM PT (2:00 PM ET)
Guest: Franco Patano, Lead product Speicalist at Databricks (LinkdIn)
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Cost: Free

Data lakehouses are becoming increasingly popular to provide a centralized, scalable analytics platform to support a wide range of data-driven workloads.

Several computing platforms such as Apache Hadoop and Apache Spark have emerged to provide a cost-effective way to store and process large amounts of data.

In addition, many managed data lake solutions also emerged to make it easier for enterprises to get started with big data analytics. For instance, Azure data lake is a popular managed data lake solution that helps customers process and analyze large amounts of data using Hadoop, Spark, and other big data technologies.

However, pressing concern about data lakes is their performance. To get the most out of a data lake, carefully design and optimize the data architecture.

A data lakehouse is a new class of data architecture that unifies the capabilities of a data lake and a data warehouse.

In this session, Franco Patano will discuss improving business decisions and self-service BI through a data lakehouse and semantic layer.

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