Use this guide to 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 engine. You will know how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For example, you can stream large volumes of data from Apache Spark in real time while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database.
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Ben Weissman is the owner and founder of Solisyon, a consulting firm based in Germany and focused on business intelligence, business analytics, and data warehousing as well as forecasting and budgeting. He is a Microsoft Data Platform MVP, the first German BimlHero, and has been working with SQL Server since SQL Server 6.5. If he is not currently working with data, Ben is probably traveling and exploring the world, running, or enjoying delicious food. You can find Ben on Twitter at @bweissman.
Enrico van de Laar has been working with data in various formats and sizes for over 15 years. He is a data and advanced analytics consultant at Dataheroes where he helps organizations get the most out of their data. He has been a Microsoft Data Platform MVP since 2014 and a frequent speaker at various data-related events all over the world. He writes about a wide variety of Microsoft data-related technologies on his blog at enricovandelaar.com. You can reach Enrico on Twitter at @evdlaar.
Use this guide to 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 engine. You will know how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For example, you can stream large volumes of data from Apache Spark in real time while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database.
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