Getting started with Microsoft Power BI – News Couple
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Getting started with Microsoft Power BI


This article was published as part of the Data Science Blogathon.

  1. an introduction
  2. What is Microsoft Power BI?
  3. Microsoft Power BI Concepts
  4. Data sources in Microsoft Power BI
  5. Import Excel data into Microsoft Power BI
  6. Query Editor
  7. Inbuilt visuals
  8. conclusion

an introduction

There is a lot of data being collected in companies and industries today. This creates the need to extract important information from this available data and turn it into insights. Data visualization makes it possible to visualize data and thus easily identify trends and patterns. There are tools and services that allow this data to be imported, edited, and visualized, and that’s where Microsoft Power BI comes in.

What is Microsoft Power BI?

Microsoft Power BI is a cloud-based business analytics service that provides interactive visualizations and business intelligence capabilities.

Business intelligence, i.e. business intelligence, consists of the strategies and techniques used to analyze data to provide historical and predictive views of data.

Microsoft Power BI allows end users to create their own charts, dashboards, and reports.

It has several major features or versions which include: Power BI Desktop, Power BI Service, Power BI Mobile Apps, Power BI Gateway, Power BI Embedded, Power BI Report Server, Power BI Premium and Power BI Visuals Marketplace.

Microsoft Power BI Concepts

These are the building blocks of Microsoft Power BI. They include data sets, reports, and dashboards. A data set is a set of related data that will be imported and processed. The report consists of visual elements such as charts and maps that Microsoft Power BI helps create from data sets. A dashboard is a group of report pages in the form of a single dashboard.

Data sources in Microsoft Power BI

Data is very important in Microsoft Power BI because it is used when it is imported and modified to create business intelligence visualizations.

Microsoft Power BI supports importing data from many data sources. Some of the popular data sources include Excel Workbook, Power BI datasets, Power BI data flow, Blank query, SQL Server, Text/CSV, Analysis services, Web, etc.

To access these data sources, tap Get data And see the contents of the drop-down list.

To view more data sources, click more… The popup shows the sources grouped under File, Database, Azure, etc.

Data sources in Microsoft Power BI 2

Import Excel data into Microsoft Power BI

Excel is a spreadsheet with rows and columns that is used to organize data while allowing its manipulation and calculations.

  • . To import Excel data, click Get data, then select excel from the dropdown menu.
  • . Select your Excel file and click Open.
  • . Navigator box opens. Click the check box to select the data that will be used for visualization. then press Pregnancy to complete.
  • . Data will be added to fields It is shown by the arrow below.
Import Excel data into Microsoft Power BI

Query Editor

The Query Editor allows the user to edit and perform transformation of data files before they are used in visualization. It allows the user to modify the data by performing actions such as removing null values, pivoting and deactivating columns, editing rows and columns, splitting and merging columns, replacing values ​​in rows, and even inverting rows.

To access the query editor, click Edit Queries.

Query Editor

There are more ways to modify the data. See below for some cases:

To make sure each data type/column is in the correct format, click on the left corner of the column heading. A drop-down menu opens where the data type can be set textAnd date/timeAnd percentage or full number, etc.

Query Editor in Microsoft Power BI

To sort columns in ascending or descending order, click on the icons shown below.

Query Editor in Microsoft Power BI 2

You can undo a step by clicking the x icon in Query settings Under Practical steps.

The Query Editor in Microsoft Power BI has applied the steps

Inbuilt visuals

These are the easily available visuals found on perceptions Part of the report page in Microsoft Power BI. Some of the visual elements include:

Linear and Clustered Column Chart

Column line chart and cluster chart is a hybrid chart that combines a line chart and a combined column chart into one visual. Charts usually have a common x-axis. Visualizes two scales with different scales.

    Microsoft Power BI Line Chart

pie chart

A pie chart depicts data in a sliced ​​pie chart. Each slice is proportional to the size it represents. The total value of the pie chart is 100%.

pie chart

line graph

A line chart consists of a series of data points linked together to form a line. A line chart can have one or more contours. They represent a trend or pattern of data and are displayed in different colors. The line chart is represented on the x and y axes and shows trends over time.

                        line graph

area chart

It consists of a line chart where the area between the axis and the line is filled with color to show the size. This graph shows the degree of change over time.

area chart

stacked vertical chart

A stacked column chart depicts data as rectangular bars on a chart. Each bar represents a value and is made up of smaller bars representing different categories.

stacked vertical chart

Treemap

An organization chart displays data in a tree-like hierarchical chart of nested rectangles. The larger the rectangle, the greater the amount of the element it represents. The rectangles are organized from largest (top left) to smallest (bottom right) and are also colored.

Treemap

waterfall outline

This chart displays the running total (that is, the sum of the values ​​of each stage before the grand total is reached) as the values ​​are increased or decreased. The columns are filled with color so it’s easy to notice the rise and fall.

waterfall outline

conclusion

In this article, we learned about data visualization and its importance. We discussed what Microsoft Power BI is, its use, and its versions. We covered the different supported data sources. There is a short tutorial on how to import Excel data. We discussed the query editor and the built-in visualizations that are available. In conclusion, we covered how to get started with it.

The media described in this article is not owned by Analytics Vidhya and is used at the author’s discretion



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