October 2021
Beginner to intermediate
322 pages
7h 27m
English
Content preview from Essential PySpark for Scalable Data Analytics
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Section 3: Data Analysis
Once we have clean and integrated data in the data lake and have trained and built machine learning models at scale, the final step is to convey actionable insights to business owners in a meaningful manner to help them make business decisions. This section covers the business intelligence (BI) and SQL Analytics part of data analytics. It starts with various data visualization techniques using notebooks. Then, it introduces you to Spark SQL to perform business analytics at scale and shows techniques to connect BI and SQL Analysis tools to Apache Spark clusters. The section ends with an introduction to the Data Lakehouse paradigm to bridge the gap between data warehouses and data lakes to provide a single, unified, scalable ...
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