Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 5.08 GB | Duration: 7h 5m

What you'll learn
Learn about data virtualization and data lakes
Learn how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database.

Learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux
Learn how to configure and deploy Big Data Clusters.
Requirements
There are no requirements or prerequisites for this course but the student should be knowledgeable in data analysis
Description
This course focuses on one of SQL Server 2019's most impactful features—Big Data Clusters. You will learn about data virtualization and data lakes for this complete artificial intelligence (AI) and machine learning (ML) platform within the SQL Server database ee. You will be shown how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For instance, you can stream large volumes of data from Apache Spark in real- while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database. This course provides everything necessary to get started working with Big Data Clusters in SQL Server 2019. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You will be shown how to configure and deploy Big Data Clusters. You will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis.
What a Big Data Cluster is
How to deploy BDC
How to analyze large volumes of data directly from SQL Server
How to analyze large volumes of data via Apache Spark
How to manage data stored in HDFS from SQL Server as if it were relational data
How to implement advanced analytics solutions through machine learning
How to expose different data sources as a single logical source using data virtualization
This course is intended for data eeers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environments.
Who this course is for
This course is intended for data eeers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environments.




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