The Ultimate Guide To Using Power BI GROUPBY Function | 3 Easy Types

GROUPBY is an underappreciated Power BI function that allows you to address common problems most straightforwardly. When you have a set of attributes that you want to group and produce an aggregate, this is the ideal solution. The GROUPBY DAX function allows you to group particular dimensions in your data and generate a table depending on the elements in your data model, which might be physical or virtual.

In this article, you will learn about Power BI GROUPBY Function and how to use it. You will also see an introduction to Power BI and its Key Features.

Table Of Contents

• What is Power BI?
  • Key Features of Power BI
• What is DAX?
• What are Power BI Functions?
• What is GROUPBY Function?
• How to Use Power BI GROUPBY Function With DAX?
  • Power BI GROUPBY Function Types: Simple Grouping
  • Power BI GROUPBY Function Types: Grouping By Multiple Columns
  • Power BI GROUPBY Function Types: Grouping With Calculations
  • Power BI GROUPBY Function Types: Additional Points
    • SUMMARIZE Function
• Conclusion

What is Power BI?

Power BI is a collection of software services, apps, and connectors that work together to turn unstructured data into logical, visually immersive, and interactive insights. Your data could be in the form of an Excel spreadsheet or a collection of Cloud-based and on-premises hybrid Data Warehouses. Connect to your data sources, visualize and uncover what matters, and share your results with whoever you choose using Power BI.

In Power BI Desktop, users can perform the following actions:

• Connect to the data.
• Transformation and modeling of the data.
• Create charts and graphs.
• Create reports and dashboards that are collections of visuals.
• Share reports with others using the Power BI service.

Key Features of Power BI

• Power BI has an Interactive Desktop: This interactive Power BI desktop solution allows you to easily access data and create reports. It is not necessary to have extensive abilities in order to make a report with this powerful tool; it is simple to understand and use. The best part of his tool is that it is completely free to download and use, allowing you to make reports without any technical expertise.
• Customize Your Visualization: Every organization is unique in how it operates and how it accomplishes its goals. There are instances when the usual route is the best option. This applies to visualization too. Due to complicated data, the Power BI tool provides a default standard that is sometimes insufficient for companies. In such cases, companies can easily utilize the custom visualization library and create a visualization that meets their requirements.
• Visibility: Data is at the heart of any business, and the fundamental difficulty that firms confront today is combining data from different sources to generate usable insights. Well, one effective technique to achieve it is to gather multiple datasets and visually organize them for better understanding. This form aids in the delivery of more in-depth knowledge of the data, allowing businesses to get a competitive advantage over their competitors.
• Data Sources: Users can choose from a variety of data sources using the Get Data tool in Power BI. The data sources can be on-premises or in the cloud, unstructured or structured. Every month, a new data source is added. For example, Excel, Power BI Datasets, Power BI Dataflows, etc are a few data sources available.
• Filtration of Datasets: You can filter the datasets to create smaller subsets with only the most relevant facts and context. Excel, SQL databases, Oracle, Azure, Facebook, Salesforce, and MailChimp are just a few of the data connectors available in Power BI. Users can connect to these data sources with ease and generate datasets by importing data from one or more sources.
• DAX Functions: The DAX functions in Power BI are Data Analysis Expressions. These analysis functions are predefined codes for performing analytics-specific data functions. Currently, the Power BI function library has over 200 functions. The creators continue to add additional ones.

What is DAX?

Data Analysis Expressions, or DAX, are expressions or formulas that are used to analyze and calculate data. These expressions are a set of functions, operators, and constants that are evaluated as a single formula to get results. DAX formulae are highly valuable in BI solutions like Power BI because they allow Data Analysts to get the most out of the data sets they have.

Analysts can use the DAX language to come up with new ways to calculate data values and come up with new insights. It’s understandable to wonder why DAX is so crucial to master to operate productively with Power BI. Creating reports in Power BI using the Data importing, manipulating, and visualizing features is a breeze. To build a quality report with all of the accessible data, a user must have a basic understanding of the Power BI Desktop. However, DAX is required to perform certain actions on the data and make very effective Power BI reports.

What are Power BI Functions?

Here are a few Power BI DAX Functions:

• LOOKUP(): Vlookup in Microsoft Excel is very similar to the LOOKUP function. Our dataset’s third table offers information on all of the managers by area. This is when LOOKUP comes into play. The ‘Manager’ column in the ‘users’ table can be compared to the corresponding ‘Region’ column in the ‘orders’ table.
• CALCULATE() and FILTER(): The DAX in the next example is similar to the group by function. It aggregates a column dynamically based on the filter. When we’re constructing a table in Power BI dashboards and simply need to filter one column, this comes in handy (while the remaining column remains unaffected by the filter). You want to calculate the sum of sales by region. The filter function divides the region column into four categories: North, South, East, and West. The aggregate of sales is then calculated based on the segregation. We’re using a measure here because an area can include any amount of rows.

• Aggregate Functions: MIN, MAX, SUM, SUMX are all aggregate functions in DAX.
• Counting Function: There are several counting functions in DAX like COUNT, COUNTROWS, COUNTA, etc.
• Logical Functions: There are multiple logical functions like AND, OR, NOT, IF, etc.

What is GROUPBY Function?

The Power BI GROUPBY function is identical to the SUMMARIZE function. GROUPBY, on the other hand, does not perform an implicit CALCULATE for any extension columns it adds. In the extension columns that GROUPBY introduces, a new function called CURRENTGROUP can be utilized inside aggregation functions. In a single table scan, Power BI GROUPBY Function is utilized to achieve several aggregations.

Here’s the syntax for Power BI GROUPBY Function:

GROUPBY (<table> [, <groupBy_columnName> [, <groupBy_columnName> [, …]]] [, <name>, <expression> [, <name>, <expression> [, …]]])

How to Use Power BI GROUPBY Function With DAX?

Now that you have a general idea of how the Power BI GROUP BY DAX function works, you will be learning how to use it with DAX in this section. In DAX, it creates groups or subtotals (works similarly to Pivot Tables).

This table will be used with cars that can be grouped by different columns.

Power BI GROUPBY Function Types: Simple Grouping

Here, you are going to group the table based on Brands i.e. by creating a list of brands.

• The first step in using Power BI GROUPBY Function is creating a new calculated table and defining it as follows:

List of brands = GROUPBY(
  cars,
  cars[Brand])

The syntax uses:

• Name of the table.
• Name of the column you are using for grouping.

Power BI GROUPBY Function Types: Grouping By Multiple Columns

Suppose you want to group the table not only on Brands but also on the Models column. Then, follow the given steps:

• To use Power BI GROUPBY Function to reference two columns, use the following format:

List of brands and models = GROUPBY(
  cars,
  cars[Brand],
  cars[Model])

Now the syntax uses the following parameters:

• Name of the table.
• All columns being used for grouping.

Power BI GROUPBY Function Types: Grouping With Calculations

You can also add SUM or COUNT Functions to the Power BI GROUPBY Function in the following way:

List of brands and models and prices = GROUPBY(
  cars,
  cars[Brand],
  cars[Model],
  "Total price",
  SUMX(
      CURRENTGROUP(),
      cars[ Price ]))

Now the syntax contains these parameters:

• Name of the table.
• All columns that are used for grouping.
• Name of the first calculated column.
• Calculations, using such functions as COUNTX, SUMX… combined with CURRENTGROUP.
• Name and calculation for the other column etc.

Power BI GROUPBY Function Types: Additional Points

This section talks about functions that are similar to Power BI GROUPBY Function and a few additional points.

SUMMARIZE Function

A table is always the outcome of SUMMARIZE. That is, it can be used to create a new table in data models, or it can be used in conjunction with other functions to create a new measure or column – as long as the outcome is a single number.

Power BI GROUPBY Function and SUMMARIZE can be simply used to get the number of unique values, based on multiple columns.

Conclusion

In this article, you have learned about Power BI GROUPBY Function, the main features of Power BI, Dax Functions and how to use them.

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