Data Visualization in Microsoft Power BI


  1. Introduction.
  2. How to create a table.
  3. How to create a Power BI pie chart.
  4. Creating a line chart in Power BI.
  5. Report creation.
  6. Conclusion.


The final article will take us through Power BI Visualizations and how to create them using the data sets created previously in these series. The walkthrough will cover 3 basic Visualizations: Table, Pie Chart, and Line Chart. These will then combine to create a basic report/dashboard within Power BI.

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Analytic Functions in SQL Server

Aggregate and Analytic functions in SQL Server operate on a set of rows. However, unlike such aggregate functions as sum, count and average that return scalar values, analytic functions return a group of rows that can be further analyzed. In this article, we will see some of the most commonly used analytic functions in SQL server. We will be discussing the following functions:

  • LEAD
  • LAG

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Applying SQL Transformations and Handling Missing Values in Azure ML

In this article, we will introduce SQL transformations in action. We will also see how to handle missing values in our dataset.

Consider a scenario of a movie rating dataset containing records of different movies along with the average user ratings associated with each movie. The ratings are in numeric form ranging from 1 to 10 with 1 as the lowest rating and, respectively, 10 as the highest rating (though no movie in the history has achieved 10 rating:). Suppose that we want to convert the numeric ratings into categorical ratings. For instance, we want to replace ratings of 1-3 with the categorical value “poor”, of 4-6 with “average” while ratings of 7-10 will have the value “good”. We can accomplish it with SQL transformation in Azure ML Studio. Read More