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Microsoft Power BI Basic ( Data visualization)

August 15, 2020

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Machine Learning in SQL Server 2017

SQL Server R Services has been renamed SQL Server Machine Learning Services , to reflect support for Python in addition to the R language. You can use Machine Learning Services (In-Database) to run R or Python scripts in SQL Server, or install Microsoft Machine Learning Server (Standalone) to deploy and consume R and Python models that don't require SQL Server. SQL Server developers now have access to the extensive Python ML and AI libraries available in the open-source ecosystem, along with the latest innovations from Microsoft: revoscalepy - This Python equivalent of RevoScaleR includes parallel algorithms for linear and logistic regressions, decision tree, boosted trees and random forests, as well as a rich set of APIs for data transformation and data movement, remote compute contexts, and data sources. microsoftml - This state-of-the-art package of machine learning algorithms and transforms with Python bindings includes deep neural networks, fast decision trees and

Tips to Increase SQL Server Query Performance

1. Create indexes 2. Create clustered indexes 3. Create non-clustered indexes 4. Drop indexes that are not used 5. Use table partitioning 6. Use temp table and table variables where ever necessary . Do not query on master table 7. Avoid the use of cursors 8. Evaluate the execution plan 9. Rebuild indexes periodically 10. Remove outer joins 11. Remove unnecessary tables 12. Only select Fields which you need 13. Do not use NOT IN clause 14. Use SET NOCOUNT ON with DML operations 15. Aviod use of Group by , order by and distinct 16. Use Try and Catch block 17. Avoid multiple joins Happy learning :)

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Microsoft Power BI Basic ( Data visualization)

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