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it's exciting to see such integration with MSSQL<br />
<br />
I would think documentation at Microsoft is the best as the entering point.<br />
&nbsp;<br />
What's new in SQL Server Machine Learning Services<br />
<a href="https://docs.microsoft.com/en-us/sql/advanced-analytics/what-s-new-in-sql-server-machine-learning-services?view=sql-server-2017" rel="ugc">https://docs.microsoft.com/en-us/sql/advanced-analytics/what-s-new-in-sql-server-machine-learning-services?view=sql-server-2017</a><br />
<br />
and check the links of articles at the left panel for more details.
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it's exciting to see such integration with MSSQL

I would think documentation at Microsoft is the best as the entering point.
 
What's new in SQL Server Machine Learning Services
https://docs.microsoft.com/en-us/sql/advanced-analytics/what-s-new-in-sql-server-machine-learning-services?view=sql-server-2017 [https://docs.microsoft.com/en-us/sql/advanced-analytics/what-s-new-in-sql-server-machine-learning-services?view=sql-server-2017]

and check the links of articles at the left panel for more details.

motioneye

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Guys,<br />
I like to know how and at what scenarios Pythons and R that embedded in sql server 2017 can really meaningful to be use? I'm still using sql 2014 and running sql reporting services to produces end report to customer &nbsp;and I can says 100% of data analysis that we have performed &nbsp;were generated from T-sql.<br />
Actually I wonder how this R and Python in sql 2017 would assist me to speed up or create more meaningful data for customer as from my experiences T-sql is doing more than enough for me to provides even complex reports to end users.<br />
If anyone &nbsp;here are able to shed some lights I maybe have more explanation and reason to upgrade to sql 2017.
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Guys,
I like to know how and at what scenarios Pythons and R that embedded in sql server 2017 can really meaningful to be use? I'm still using sql 2014 and running sql reporting services to produces end report to customer  and I can says 100% of data analysis that we have performed  were generated from T-sql.
Actually I wonder how this R and Python in sql 2017 would assist me to speed up or create more meaningful data for customer as from my experiences T-sql is doing more than enough for me to provides even complex reports to end users.
If anyone  here are able to shed some lights I maybe have more explanation and reason to upgrade to sql 2017.

SQL 2014 T-sql vs R and Phyton in sql 2017, is it worth upgrades

Microsoft SQL Server is a suite of relational database management system (RDBMS) products providing multi-user database access functionality.SQL Server is available in multiple versions, typically identified by release year, and versions are subdivided into editions to distinguish between product functionality. Component services include integration (SSIS), reporting (SSRS), analysis (SSAS), data quality, master data, T-SQL and performance tuning.

Microsoft SQL Server

Statistical packages are software titles, such as JMP and GNU Octave, and programming languages, such as MATLAB, R and SAS, that are used to discover, explore and analyze data and suggest useful conclusions, either to learn something unexpected or to confirm a hypothesis. The field includes the design and analysis of techniques to give approximate but accurate solutions to hard problems in statistics, econometrics, time-series, optimization and 2D- and 3D-visualization. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

Statistical Packages

R is a programming language and environment used primarily for statistical data analysis.

SQL (Structured Query Language) is designed to be used in conjunction with relational database products as of a means of working with sets of data. SQL consists of data definition, data manipulation, and procedural elements. Its scope includes data insert, query, update and delete, schema creation and modification, and data access control.