R

Esat Erkec

How to use JSON data in Azure Machine Learning

November 9, 2018 by

Azure Machine Learning (also known as Azure ML) is cloud-based machine learning solution of Microsoft. Microsoft Azure Machine Learning is a fully-managed cloud-based service that provides the ability to create and train predictive analytic solutions. Another advantage of Azure ML is that you can access and easily make changes anywhere in machine learning models with help of Microsoft Azure Machine Learning Studio.

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Esat Erkec

How to use JSON data in SSRS

November 6, 2018 by

In this article, we will explore the concept of using JSON data in SQL Server Reporting Services (SSRS). This usage concept will include a different approach than the usual methodologies because we will take advantage of SQL Server R service support.

What is JSON?

JSON is an abbreviation for JavaScriptObjectNotation. The main purpose of JSON data was to provide data transfer between server and web applications for JavaScript but today’s JSON is the most popular data interchange format. JSON offers two advantages to us. These are; light-weight text based format easily readable by humans. Currently, JSON is not only used in JavaScript applications, it is also used in all popular software programing languages like JavaScript, C++, C#, Perl, Java, Python, Php etc.

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Ben Richardson

Machine Learning Services – Configuring R Services in SQL Server

October 25, 2018 by

The R language is one of the most popular languages for data science, machine learning services and computational statistics. There are several IDEs that allow seamless R development. Owing to the growing popularity of the R language, R services have been included by Microsoft in SQL Server 2016 onwards. In this article, we will briefly review how we can integrate R with SQL Server 2017. We will see the installation process and will also execute the basic R commands in SQL Server 2017.

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Esat Erkec

How to create advanced analytics using Power BI and R scripts

February 27, 2018 by

In this article, we will discover how to find the associations and hidden patterns in a dataset. The tool we will use for this is Power BI and not use any statistical functions or calculation.

Explanation

Power BI is one of the most powerful business intelligence solutions in the market. A cloud-based, user-friendly interface and basic development abilities provide this solution to be more convenient for people to use.

As you may know, Microsoft now supports R script in SQL Server and Power BI. R script support opens magical gates of statistics world to Power BI. Custom Visual offers very useful and interesting visual components for Power BI. In this store, many useful visualizations have been created by Microsoft or the community itself. Some of these visuals use R script infrastructure and this feature allows us to create advanced visual analytic in Power BI. Only a Power BI account is enough to connect and download theses visuals. We will use these visuals in our examples.

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Sifiso W. Ndlovu

How to plot a SQL Server 2017 graph database using SQL Server R

January 3, 2018 by

A few years ago, one common business case I came across in my professional career that required modelling of data into a many-to-many entity relationship type was the representation of a consultants and their projects. Such a business case became a many-to-many entity relationship type because whilst each project can be undertaken by several consultants, consultants can in turn be involved in many different projects. When it came to storing such data in a relational database engine, it meant that we had to make use of bridging tables and also make use of several self-joins to successfully query the data.

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Esat Erkec

R script word-cloud in SQL Server Report Builder

November 28, 2017 by

What is R

R is a very popular data programing language. R is especially used in data analysis, statistics calculations, predictions, data mining and machine learning. R is used by data scientist, economist, genetic scientists, and statisticians. R has very wide usage in real life. Healthcare, finance, marketing, and manufacturing are some of them.

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