Python

Prashanth Jayaram

What’s new in SQL Server 2017

August 14, 2018 by

SQL Server 2017 is considered a major release in the history of the SQL Server life cycle for various reasons. From my personal point of view, SQL Server 2017 is indeed an interesting release. After writing lot about it and testing various features of SQL Server 2017, I’d like to walk you through some of its interesting features.

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Prashanth Jayaram

The importance of Python in SQL Server Administration

January 8, 2018 by

Some of my previous articles on Python provided insight of the basics and the usage of Python in SQL Server 2017.

This article is an effort to collect all the missing pieces and try to showcase the importance of using Python programming in SQL Server.

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Gerald Britton

Get more out of Python on SQL Server 2017

January 5, 2018 by

Introduction

One of the new features announced with SQL Server 2017 is support for the Python language. This is big! In SQL Server 2016, Microsoft announced support for the R language – an open source language ideally suited for statistical analysis and machine learning (ML). Recognizing that many data scientists use Python with ML libraries, the easy-to-learn-hard-to-forget language has now been added to the SQL Server ML suite.

There’s a big difference between R and Python though: R is a domain-specific language while Python is general purpose. That means that the full power of Python is available within SQL Server. This article leaves ML aside for the moment and explores a few of the other possibilities.

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Prashanth Jayaram

Data Interpolation and Transformation using Python in SQL Server 2017

November 21, 2017 by

As a continuation to my previous article, How to use Python in SQL Server 2017 to obtain advanced data analytics, a little bit of curiosity about Deep Learning with Python integration in SQL Server led me to write this latest article.

With Python running within SQL Server, you can bring the existing data and the code together. Data is accessible directly, so there’s no need to extract query data sets, moving data from storage to the application. It’s a useful approach, especially considering issues of data sovereignty and compliance, since the code runs within the SQL Server security boundaries, triggered by a single call from T-SQL stored procedures.

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Prashanth Jayaram

An overview of Python vs PowerShell for SQL Server Database Administration

November 2, 2017 by

Today, Microsoft claims that Linux runs like a First-Class citizen on Azure, .NET Core has been open-sourced, and has been ported over to Linux, taking PowerShell along. PowerShell runs really well on Ubuntu, CentOS, RedHat Linux, and even Mac OS X. There are Alpha builds available for a few other platforms as well, all available for exploitation under the MIT License on GitHub. “Manage anything, anywhere” is what Microsoft is offering to its customers. Keeping with that, we now have:

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Prashanth Jayaram

Why would a SQL Server DBA be interested in Python?

October 23, 2017 by

If we follow blogs and publications on the technological advancement with respect to SQL, we notice the increase in the number of references to Python, of late. Often, that makes us think:

  • Why so much emphasis on Python these days?
  • Isn’t knowing PowerShell scripting sufficient for the automation requirements of today?
  • Is it the time DBAs started learning a programming language such as Python in order to handle their day-to-day tasks more efficiently?
  • Why do so many job postings these days include “knowledge of scripting” as a requirement?
  • Is all of this happening because the paradigm is shifting? Can’t the current Microsoft-specific languages such as PowerShell handle the shift?
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Prashanth Jayaram

How to use Python in SQL Server 2017 to obtain advanced data analytics

June 20, 2017 by

On the 19th of April 2017, Microsoft held an online conference called Microsoft Data Amp to showcase how Microsoft’s latest innovations put data, analytics and artificial intelligence at the heart of business transformation. Microsoft has, over the last few years, made great strides in accelerating the pace of innovation to enable businesses to meet the demands of a dynamic marketplace and harness the incredible power of data—more securely and faster than ever before.

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