Power BI is a Business Intelligence (BI) tool offered by Microsoft that provides you with real-time high-level analytics, extensive modeling, and custom development. It has led the charge in making business analysis more efficient through services that are intuitive, interactive, and easy to use.
This article talks about the different methods you can follow to transform data in Power BI seamlessly. It also discusses the importance of Transform Data Power BI along with a brief introduction to the salient features of Power BI before delving into Power BI Transform Data methods.
Table of Contents
What is Power BI?
Power BI is a Business Intelligence product from Microsoft. It allows users to look at data from many sources and build Reports and Dashboards. It can be used as a stand-alone desktop application or as a fully managed web service hosted in the cloud. While the Power BI Desktop is available for free, the Power BI Service is a subscription-based service that charges users based on how much they use it.
Microsoft has released Power BI Mobile for customers who want to keep an eye on their data while on the go. Power BI may also be used to add analytical tools to custom web apps. It’s compatible with the vast majority of Microsoft’s enterprise software.
Power BI takes advantage of the ability to connect to the most common databases outside of the Microsoft ecosystem and create simple, Interactive Dashboards from them.
Key Features of Power BI
Power BI has a large number of capabilities that set it apart from other BI applications. The following are some of these characteristics:
- You may use a range of Graphical Elements to design your Dashboards. The Dashboards can be printed and shared.
- In Power BI, you may filter your datasets to focus on smaller datasets first. This allows you to concentrate on certain data rather than the full dataset all at once.
- Power BI can connect to most common databases outside of the Microsoft environment and produce easy, interactive dashboards from them.
- It offers a huge selection of visually appealing Visualization Templates. You can create Reports and Dashboards to display your data using as simple or as complex visuals as you choose.
- Power BI has a “Get Data” tool that lets you select from a range of data sources, including On-Premise, Cloud-Based, Unstructured, and Structured data, among others. New data sources are added every month.
- Dashboards, Data Models, Datasets, Embedded Queries, and many other features are available in Power BI’s “Content Packs.” Instead of searching for the pieces separately, you can use the elements in the “Content Packs.”
What is Power BI Power Query Editor?
Power BI Power Query Editor can be used to edit or transform data files before they get loaded into the Power BI dashboard. The Query Editor serves as an intermediate data container that allows you to modify data by choosing columns and rows, pivoting and unpivoting columns, splitting columns and rows, etc.
The changes that are carried out by the Query Editor are not reflected within the actual dataset. Once, you have preprocessed the data and transformed it into the required format, you can easily load the data into the Power BI environment.
Why do you need to Transform Data in Power BI?
The data obtained from disparate sources often comes in an unformatted structure, and it requires a skill set to format the data into a suitable format and extract actionable insights from it. A tool is needed to extract and analyze the data after transforming the data into a format that allows you to analyze it seamlessly. This is where Power BI comes in handy, allowing you to transform data in an interactive and correlative manner to extract, analyze, and visualize it.
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It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on the key business needs and perform insightful analysis by using a BI tool of your choice.
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- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
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Ways to Transform Power BI Data
The transformation steps discussed in this section can be performed in any order after importing data into Power BI Query Editor. To import the data, you can follow the steps mentioned below:
- Step 1: You can go to the “Home” tab in the ribbon section and click on “Get Data” to provide you with the options to source the data from a different platform.
- Step 2: Since you have your unsorted data in Excel, choose “Excel” from the menu.
- Step 3: This will open up a window to choose the “Excel file” that you wish to upload from your device. Next, the Navigator page prompts you to select the datasheets that you wish to work with. You can accordingly check to mark the sheets you want to. Since the primary aim was to sort the data, you can go with the “Transform Data” option. You can click on Load to upload the file without any transformation.
- Step 4: Power BI Transform Data button would then take you to another window, also known as the Power BI Power Query Editor, where you will be transforming and cleaning your data.
Here are the key aspects involved in Power BI Transform Data:
How to Perform Renaming Operations in Power BI?
Renaming Data Sources in Power BI
If you take a look at the left corner of the Power BI Query Editor window, you can see an option dubbed “Queries”. Under this Power BI Transform Data session, all the different data sources are listed with the default data source’s file name, i.e., when an SQL table is loaded, the table’s name gets listed in this session, and if you load an Excel file, then it’s file name shows up.
This might be difficult for you when you have multiple data sources for a single Power BI Transform Data instance. You can then rename this data source as per your wish. All you need to do is double-click on the source and rename it as follows:
Renaming Tables in Power BI
If you are not satisfied with the name given to the Power BI Transform Data tables, you can change the name by implementing one of the two Power BI Transform Data options mentioned in the figure below. You just need to double-click the name you wish to change and specify the new name:
After changing all the table names, the result would look somewhat like this:
Renaming Power BI Columns
The simplest task in Power BI transform data is to rename the column heading. Just “Double Click” on the column heading which is highlighted with a blue mark, then you can replace the name of the column heading with a new header.
Renaming Queries in Power BI
You can rename the Power BI Transform Data query in the Query Settings pane on the right-hand side of the canvas. The Power BI Transform Data Query Settings pane also houses the ‘Applied Steps’ list. Therefore, every change you make to your data generates a new step on the list making it easier to undo any unwanted changes.
This Power BI Transform Data step can be useful when loading multiple datasets from different sources by using a descriptive name making it easy to find what you are looking for. This is even more integral when you are loading data from a database.
How to Perform Removal Operations in Power BI?
Removing Columns & Rows in Power BI
When working on a larger dataset, you do not need all the data. You can refine the data by removing unwanted columns and rows. To execute this Power BI Transform Data step in the Power BI Query Editor, you need to navigate to Choose Columns, Remove Columns, Keep Rows, and Remove Rows options as mentioned under the Home tab. By leveraging these Power BI Transform Data options, you can easily look to remove some of the unwanted data.
Removing Records with Power BI Data Filters
You can also easily remove specific rows that aren’t needed in your dataset by leveraging a Power BI Transform Data filter. The menu can help remove columns that are empty, that end or start with a specific value. Similar to the steps required to clean the dataset, this Power BI Transform Data step makes it easier to navigate for your end-user and helps them answer their questions quicker.
Removing Duplicates from Power BI Datasets
Removing duplicates comes in handy when you have to load in an unfamiliar dataset that hasn’t come from a trusted data source especially if the dataset is quite large. This Power BI Transform Data step can be done in Excel but this gets more difficult with larger datasets. This can also be done in a database but if you don’t have permission to load the data, this Power BI Transform Data might not be a good option for you.
You can remove the duplicates by right-clicking a column, and selecting the ‘remove duplicates’ option to remove any duplicates you might find in the dataset.
How to Perform Merge Operations in Power BI?
Merging Columns in Power BI
To merge two columns in Power BI, you can carry out the following steps:
- Step 1: Choose the two columns you wish to merge and go to “Add Column”.
- Step 2: Next, choose the “Merge Columns” option.
- Step 3: The previous step prompts the Merge Columns page where you can specify the specific separator for the columns and click on “OK” to finish this Power BI transform data step.
Using the Pivots in Power BI
To pivot a column, you can follow the steps mentioned below:
- Step 1: Select the column you wish to pivot.
- Step 2: On the Transform tab in the Any column group, choose the Pivot column.
- Step 3: Next, in the pivot dialog box, in the Value column list, you can choose Value.
- Step 4: By default, Power Query will try to execute a sum as the aggregation, but you can choose the Advanced option to sift through the other available aggregations before deciding on the one you like.
Unpivoting Data in Power BI
Unpivoting a column means unpacking similar values and collating them under a single heading. When you take a look at your unsorted data, you can see that all the four columns South, North, West, and East, depict the same metric. Therefore, you might want to separate it into two columns where one column shows you the Sale made and another column depicts the Region.
- Step 1: Choose all four columns, right-click on any heading, and then choose “Unpivot Columns”. This will result in two new columns, called Value and Attribute as shown below. You can rename these two columns by following the steps mentioned in the Renaming Columns section.
How to Change/Modify Data Types in Power BI?
If you wish to change the data type as a part of Power BI transform data, you can follow the steps mentioned below:
- Step 1: Select the column and “Right Click” on the column header.
- Step 2: This prompts a drop-down list from which you can select “Change Type”.
- Step 3: When you select it, a drop-down list appears with a list of different data types to choose from. You can choose the data type you like, say Fixed Decimal Number. Here are the results for the same:
How to Format Text & Replace Values in Power BI?
You can find the replace values option on the ‘Transform’ tab of the ribbon. The advanced menu provides you with the option to insert special characters to match the entire cell contents. This might come in handy since datasets may be loaded with typos that need cleaning up or values that aren’t as detailed as expected.
You can find formatting options in the ‘Transform’ tab of the ribbon that can be used to clean, trim, and change the case of the text. This can come in handy because cleansing text fields make it easier to execute and read further transformations. The ‘Trim’ option is especially handy when you want to remove any trailing or leading spaces.
This blog talks about the different methods you can use to implement Power BI Transform Data seamlessly. It also gives a brief introduction to the salient features of Power BI, Power BI Query Editor, and the importance of Power BI Transform Data for efficient data operations for your business use case.
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