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You're reading from  SQL Server 2017 Machine Learning Services with R.

Product typeBook
Published inFeb 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781787283572
Edition1st Edition
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Authors (2):
Julie Koesmarno
Julie Koesmarno
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Julie Koesmarno

Julie Koesmarno is a senior program manager in the Database Systems Business Analytics team, at Microsoft. Currently, she leads big data analytics initiatives, driving business growth and customer success for SQL Server and Azure Data businesses. She has over 10 years of experience in data management, data warehousing, and analytics for multimillion-dollar businesses as a SQL Server developer, a system analyst, and a consultant prior to joining Microsoft. She is passionate about empowering data professionals to drive impacts for customer success and business through insights.
Read more about Julie Koesmarno

Tomaž Kaštrun
Tomaž Kaštrun
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Tomaž Kaštrun

Toma Katrun is a SQL Server developer and data scientist with more than 15 years of experience in the fields of business warehousing, development, ETL, database administration, and query tuning. He holds over 15 years of experience in data analysis, data mining, statistical research, and machine learning. He is a Microsoft SQL Server MVP for data platform and has been working with Microsoft SQL Server since version 2000. He is a blogger, author of many articles, a frequent speaker at the community and Microsoft events. He is an avid coffee drinker who is passionate about fixed gear bikes.
Read more about Tomaž Kaštrun

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Summary

Using SQL Server R for any kind of DBA task, as we have seen here, it is not always hardcore statistics or predictive analytics; we might also be some simple statistical understanding underlying the connection and relationships between the attribute's queries, gathered statistics, and indexes. Prognosing and predicting, for example, information from execution plans in order to prepare a better understanding of the query of cover missing index, is a crucial point. Parameter sniffing or a cardinality estimator would also be a great task to tackle along the usual statistics.

But we have seen that predicting events that are usually only monitored can be a huge advantage for a DBA and a very welcome feature for core systems.

With R integration into SQL Server, such daily, weekly, or monthly tasks can be automated to different, before not uses yet, extent. And as such,...

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SQL Server 2017 Machine Learning Services with R.
Published in: Feb 2018Publisher: PacktISBN-13: 9781787283572

Authors (2)

author image
Julie Koesmarno

Julie Koesmarno is a senior program manager in the Database Systems Business Analytics team, at Microsoft. Currently, she leads big data analytics initiatives, driving business growth and customer success for SQL Server and Azure Data businesses. She has over 10 years of experience in data management, data warehousing, and analytics for multimillion-dollar businesses as a SQL Server developer, a system analyst, and a consultant prior to joining Microsoft. She is passionate about empowering data professionals to drive impacts for customer success and business through insights.
Read more about Julie Koesmarno

author image
Tomaž Kaštrun

Toma Katrun is a SQL Server developer and data scientist with more than 15 years of experience in the fields of business warehousing, development, ETL, database administration, and query tuning. He holds over 15 years of experience in data analysis, data mining, statistical research, and machine learning. He is a Microsoft SQL Server MVP for data platform and has been working with Microsoft SQL Server since version 2000. He is a blogger, author of many articles, a frequent speaker at the community and Microsoft events. He is an avid coffee drinker who is passionate about fixed gear bikes.
Read more about Tomaž Kaštrun