Machine learning with Microsoft SQL server

 Machine learning with Microsoft SQL server  

Microsoft has been always known as a company who walk with the era because they develop significantly awesome products with mind-blowing features and an extensive amount of them, Like SQL Server(DB & DWH), Power BI for Reporting, SQL Server Database and SSDT (SQL Server data tools).  

In the world of BI (Business Intelligence), Microsoft can be considered as one of the leading organizations because it is covering almost 23% of the market in terms of giving services and product with SQL server DB and other BI Tools. 

Microsoft always has been very upfront in providing new exciting features for developers, all the latest features and Microsoft gives it in their tools are in line with the needs to the developer according to current industry requirements. With continuously upgrading their product with the latest features and making life easy for developers like us. 

Microsoft SQL Server + Machine Learning: 

Microsoft has been always known as a company which walks with the Era, because they develop significantly remarkable products with extensive features, like Power BI for Reporting, SQL Server Database and SSDT (SQL Server Data Tools), and other tools in Business intelligence field. 

Microsoft SQL Server has recently introduced support for Python and R for Data Science and ML Modeling in SQL Server 2017 version and continuously developing support for Python and R language by providing the extensive feature. 

Python & R can be used to provide advanced analytics solution to modern business problems like  

• Performing Advance ETL which is not possible with Basic SQL. 

• Fraud detection for credit cards 

• Advance product promotion analysis 

• Generating Predictive Analysis and Reports for Business 

• 
  

Prerequisites: - 

• SQL server 2017 or above 

• Python and R services (this needs to be installed while installing SQL server) 

Following are the Python and R version provided in SQL Server. 

 

 

Note: Microsoft SQL Server provides Continuum Analytics Python package which includes several different Python models for Data Science and Advanced Analytics like Pandas, Sklearn, Numpy etc. If a new python module is required for our analysis, then it can be installed with PIP. 

 

In Database Python Integration: 

With the full support of all python feature in SQL Server, now Data engineers and Scientist can leverage the full capability of SQL server with python to design and develop complex pipelines and Machine learning models. 

Python operationalization with T-SQL:  In this mode, python script can be executed in SQL Server itself by calling sp_execute_external_script  with a required script. Any external application can call TSQL with parameters and get expected outputs. 

 

 

 

Python remote computes in SQL Server:  

With SQL server remote computes method user can push code to SQL server and do the computation in the SQL server.  

 

Step1: Sending to code SQL server execution environment 

Step2: Execution part gets computed in SQL server  

Step3: Getting back the results. 

In-database Python integration is not limited to just machine learning and AI solutions – it is equally useful for general purpose data analysis work by combining Python and SQL in powerful ways like leveraging strengths of respective languages. 

 

Conclusion: 

As Data Science and Machine Learning are emerging technologies in today’s era, every business wants to get maximum ROI (Return on Investments) by using Advanced Analytics. Microsoft is focusing on providing the best solution for their current products like Power BI, SQL Server, SSRS, SSAS and SSIS to make BI (Business Intelligence) more efficient and effective. 

Microsoft is continuously enhancing SQL server capabilities in a preview of SQL server 2019 version Microsoft providing support for HDFS and Spark framework support for simplifying big data analytics for SQL Server users.