Description:Analysis and machine learning models are only as good as the data they're built on. Querying processed data and getting insights from it requires a robust data pipeline--and an effective storage solution that ensures data quality, data integrity, and performance.This guide introduces you to Delta Lake, an open-source format that enables building a lakehouse architecture on top of existing storage systems such as S3, ADLS, GCS, and HDFS. Delta Lake enhances Apache Spark and makes it easy to store and manage massive amounts of complex data by supporting data integrity, data quality, and performance. Data engineers, data scientists, and data practitioners will learn how to build reliable data lakes and data pipelines at scale using Delta Lake.Understand key data reliability challenges and how to tackle themLearn how to use Delta Lake to realize data reliability improvementsConcurrently run streaming and batch jobs against your data lakeExecute update, delete, and merge commands against your data lakeUse time travel to roll back and examine previous versions of your dataLearn best practices to build effective, high-quality end-to-end data pipelines for real world use casesIntegrate with other data technologies like Presto, Athena, Redshift and other BI toolsLearn how thousands of companies are processing exabytes of data per month with their lakehouse architecture using Delta Lake.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes. To get started finding Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.
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PDF, EPUB & Kindle Edition
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ISBN
1098151909
Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes
Description: Analysis and machine learning models are only as good as the data they're built on. Querying processed data and getting insights from it requires a robust data pipeline--and an effective storage solution that ensures data quality, data integrity, and performance.This guide introduces you to Delta Lake, an open-source format that enables building a lakehouse architecture on top of existing storage systems such as S3, ADLS, GCS, and HDFS. Delta Lake enhances Apache Spark and makes it easy to store and manage massive amounts of complex data by supporting data integrity, data quality, and performance. Data engineers, data scientists, and data practitioners will learn how to build reliable data lakes and data pipelines at scale using Delta Lake.Understand key data reliability challenges and how to tackle themLearn how to use Delta Lake to realize data reliability improvementsConcurrently run streaming and batch jobs against your data lakeExecute update, delete, and merge commands against your data lakeUse time travel to roll back and examine previous versions of your dataLearn best practices to build effective, high-quality end-to-end data pipelines for real world use casesIntegrate with other data technologies like Presto, Athena, Redshift and other BI toolsLearn how thousands of companies are processing exabytes of data per month with their lakehouse architecture using Delta Lake.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes. To get started finding Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.