Power Query to Power BI: Load, Clean & Analyze Multi Level Data in Power BI Quickly & Easily
Learn the hidden Tips, Tricks & Techniques to Load and Clean Dirty Data within a few Clicks in Power Query (in Power BI), and then Analyze the data in useful visualization charts, tables, maps in a pretty dashboard for the management.
Slice the data by the year, Country, Category or a combination of these easily.
This Power Query & Power BI tutorial video is recorded by Vinai Prakash, creator or @ExcelChamp and founder of ExcelChamp.Net site.
This Step by Step Tutorial on How to Clean the Dirty Data with multiple levels of information, but without any headings, and then how to create data visualizations in Power BI Dashboards.
We will show you how to:
- How to load an Excel sheet in Power BI
- How to Clean the Data in Power Query (within Power BI)
- How to Undo a few automatically done steps within Power Query
- Transpose a whole table in Power Query
- How to fill missing values from the values provided from the rows above.
- How to promote the First Row Headers to be the Column Headers in Power Query
- How to flip the columns into rows by using the Unpivot Other Columns command in Power Query
- How to Change the Column Headings to be more appropriate
- How to rename a Query within Power Query
- How to change the data type of any column of data in Power Query
- How to Close and Apply in Power Query to finish the loading of data to Power BI
- How to create simple Table visualizations in Power BI
- How to add a Pie Chart in Power BI Visualizations
- How to Style and Format a Table values, and how to format numeric values in Power BI
- How to Add a Map Visualization in Power BI
- How to Add a Slicer in Power BI Dashboard
- How to Use values in any Visualization to Slice and Cross Filter other Visualizations and charts.
- How to add a nice heading to your Power BI Dashboard
- How to change the Page name in Power Bi
- How to Analyze the Completed Dashboard in Power BI
- What happens when new data arrives. How to add new data to the Excel Data file
- How to get the latest data to appear in the Power BI Dashboard in a single click
- Beginning of full data analysis.
This mini, step by step Power Query and Power BI Tutorial by @ExcelChamp Vinai Prakash has been created to demonstrate the powerful features built within Power Query and Power BI Data Visualizations.
What is Power Query in Power BI?
Power Query is a data transformation and data preparation tool available in Microsoft Power BI, Excel, and other Microsoft products. It is a powerful and flexible tool that allows users to connect, combine, and refine data from various sources to create clean, structured, and analytically useful data sets.
Here are some key features and functionalities of Power Query in Power BI:
Data Source Connectivity: Power Query supports a wide range of data sources, including databases, Excel files, SharePoint lists, web pages, OData feeds, JSON, XML, and many others. It simplifies the process of connecting to these diverse data sources and importing data.
Data Transformation: With Power Query, you can perform various data transformation operations like filtering, sorting, grouping, pivoting, unpivoting, merging, appending, and more. It enables you to clean, reshape, and enrich your data before loading it into Power BI for analysis.
Query Editor: Power Query provides a user-friendly Query Editor interface where you can visually build data transformation steps. You can see a preview of your data at each transformation step and easily modify the applied steps to achieve the desired data structure.
Applied Steps: Each data transformation operation in Power Query is recorded as an “Applied Step.” This means that all the data cleaning and manipulation actions you perform in the Query Editor are stored sequentially in the Query Settings, and you can revisit and modify any step at any time.
M Language: Power Query uses the M language behind the scenes to define the data transformation steps. While most users can leverage the Query Editor’s visual interface without writing any code, advanced users can also dive into the M code to perform custom transformations and create more complex queries.
Data Load: After you’ve applied all the necessary data transformations, you can load the cleaned data into Power BI’s data model for further analysis and visualization.
By utilizing Power Query in Power BI, you can significantly reduce the time and effort required to prepare data for analysis, ensuring that you work with clean and reliable datasets that are ready for insightful reporting and visualization.
Why Should You Learn Data Visualization With Power BI?
Learning Power Query, DAX Formulas, and Power BI data visualization offers several compelling reasons for individuals and organizations:
Data Transformation and Cleaning: Power Query allows you to import data from various sources and perform data transformation and cleaning tasks efficiently. It helps streamline the data preparation process, ensuring data accuracy and consistency.
Advanced Data Modeling: DAX (Data Analysis Expressions) enables you to create powerful data models and perform complex calculations on the data. It allows for creating calculated columns, measures, and calculated tables, providing deeper insights into the data.
Seamless Data Integration: Power BI integrates seamlessly with numerous data sources, databases, and online services. Learning Power Query and DAX makes it easier to bring in data from diverse sources and create a unified view for analysis.
Enhanced Data Visualization: Power BI’s data visualization capabilities are robust and intuitive. Learning data visualization techniques helps you represent data in compelling ways, making it easier to derive insights and communicate findings effectively.
Interactive Dashboards: Power BI enables the creation of interactive and dynamic dashboards. By mastering these tools, you can build engaging dashboards that allow users to explore data and gain actionable insights in real-time.
Informed Decision-Making: With Power Query, DAX, and Power BI data visualization skills, you can transform raw data into meaningful information. This empowers decision-makers to make data-driven decisions, leading to improved business outcomes.
Career Opportunities: Power Query, DAX, and Power BI are widely used in industries and organizations for data analysis and reporting. Acquiring these skills enhances your employability and opens up career opportunities in data analytics and business intelligence roles.
Time and Cost Efficiency: Learning these tools can lead to more efficient data analysis and reporting processes. Automated data transformation, advanced calculations, and interactive visualizations save time and resources, increasing overall productivity.
Scalability and Flexibility: Power BI is a scalable tool that can handle large datasets and complex data models. Learning its features allows you to work with diverse data scenarios and adapt to different business needs.
Stay Ahead in the Industry: In today’s data-driven world, being proficient in Power Query, DAX, and Power BI data visualization gives you a competitive edge. It positions you as a valuable asset in any organization looking to leverage data for growth and success.
Learning Power Query, DAX Formulas, and Power BI data visualization is a strategic investment in your professional development, providing the skills and tools needed to excel in the realm of data analytics and business intelligence.
Invest in your future.
Founder & Principal Trainer of ExcelChamp.Net