Power BI – Tutorial Notes
Power BI is a powerful tool for creating interactive visualizations from data. To get
started, you’ll need to connect your data sources. Here’s a general guide on how to do
that:
Get Data:
● Click on the “Get Data” button on the Home ribbon.
● You’ll see a variety of data sources to choose from. Some common options
include:
● File: For Excel, CSV, JSON, and other file formats.
● Database: For SQL Server, Oracle, MySQL, and other databases.
● Online Services: For Azure SQL Database, Salesforce, Google Analytics, and
more.
1. Select Your Data Source:
● Choose the appropriate data source based on where your data resides.
● If prompted, provide the necessary connection details, such as:
● File path: For files.
● Server name and database: For databases.
● Authentication credentials: For online services.
2. Navigate and Choose Data:
● Depending on the data source, you may need to navigate through folders,
tables, or queries to select the specific data you want to import.
● Use the preview pane to see a sample of your data before importing.
3. Load or Transform Data:
● Once you’ve selected your data, choose whether to load it directly into Power BI
or transform it first using Power Query Editor.
● Loading: Directly imports the data into Power BI for visualization.
● Transforming: Allows you to clean, shape, and combine data before loading it.
This is often necessary for complex datasets.
Data Transformation and Cleaning
4. Data Cleansing:
● Removing duplicates: Identify and remove duplicate rows.
● Handling missing values: Fill missing values with appropriate values or remove
rows with too many missing values.
, ● Correcting data inconsistencies: Fix errors in data, such as incorrect dates or
typos.
● Data standardization: Ensure consistency in data formats and units.
5. Data Shaping:
● Changing data types: Convert data types to match your analysis needs (e.g., text
to number).
● Adding or removing columns: Create or delete columns based on your
requirements.
● Renaming columns: Change column names for clarity.
● Splitting and combining columns: Divide or merge columns as needed.
● Unpivoting and pivoting: Reshape your data from wide to tall format or vice
versa.
6. Data Enrichment:
● Joining tables: Combine data from multiple tables based on common columns.
● Merging queries: Merge the results of different queries.
● Appending rows: Add rows from one query to another.
7. Steps to Perform Data Transformation and Cleaning in Power BI:
● Load your data: Import your data source into Power BI Desktop.
● Open Power Query Editor: Click on the “Edit Query” button in the ribbon.
● Apply transformations: Use the various tools and functions in Power Query
Editor to perform the necessary transformations.
● Close and apply: Click “Close & Apply” to apply the changes to your data.
8. Example: Cleaning a Dataset with Missing Values
● Load your data: Import your dataset into Power BI Desktop.
● Open Power Query Editor: Click “Edit Query.”
● Fill missing values: In the “Transform” tab, click “Fill” and choose the
appropriate method (e.g., “Fill Down”).
● Close and apply: Click “Close & Apply.”
Designing Reports in Power BI: A Comprehensive Guide
➢ Choose a Layout:
• Select a page layout: Choose a layout that best suits your report’s
content and purpose.
• Add pages: If your report requires multiple sections, add additional
pages.
Power BI is a powerful tool for creating interactive visualizations from data. To get
started, you’ll need to connect your data sources. Here’s a general guide on how to do
that:
Get Data:
● Click on the “Get Data” button on the Home ribbon.
● You’ll see a variety of data sources to choose from. Some common options
include:
● File: For Excel, CSV, JSON, and other file formats.
● Database: For SQL Server, Oracle, MySQL, and other databases.
● Online Services: For Azure SQL Database, Salesforce, Google Analytics, and
more.
1. Select Your Data Source:
● Choose the appropriate data source based on where your data resides.
● If prompted, provide the necessary connection details, such as:
● File path: For files.
● Server name and database: For databases.
● Authentication credentials: For online services.
2. Navigate and Choose Data:
● Depending on the data source, you may need to navigate through folders,
tables, or queries to select the specific data you want to import.
● Use the preview pane to see a sample of your data before importing.
3. Load or Transform Data:
● Once you’ve selected your data, choose whether to load it directly into Power BI
or transform it first using Power Query Editor.
● Loading: Directly imports the data into Power BI for visualization.
● Transforming: Allows you to clean, shape, and combine data before loading it.
This is often necessary for complex datasets.
Data Transformation and Cleaning
4. Data Cleansing:
● Removing duplicates: Identify and remove duplicate rows.
● Handling missing values: Fill missing values with appropriate values or remove
rows with too many missing values.
, ● Correcting data inconsistencies: Fix errors in data, such as incorrect dates or
typos.
● Data standardization: Ensure consistency in data formats and units.
5. Data Shaping:
● Changing data types: Convert data types to match your analysis needs (e.g., text
to number).
● Adding or removing columns: Create or delete columns based on your
requirements.
● Renaming columns: Change column names for clarity.
● Splitting and combining columns: Divide or merge columns as needed.
● Unpivoting and pivoting: Reshape your data from wide to tall format or vice
versa.
6. Data Enrichment:
● Joining tables: Combine data from multiple tables based on common columns.
● Merging queries: Merge the results of different queries.
● Appending rows: Add rows from one query to another.
7. Steps to Perform Data Transformation and Cleaning in Power BI:
● Load your data: Import your data source into Power BI Desktop.
● Open Power Query Editor: Click on the “Edit Query” button in the ribbon.
● Apply transformations: Use the various tools and functions in Power Query
Editor to perform the necessary transformations.
● Close and apply: Click “Close & Apply” to apply the changes to your data.
8. Example: Cleaning a Dataset with Missing Values
● Load your data: Import your dataset into Power BI Desktop.
● Open Power Query Editor: Click “Edit Query.”
● Fill missing values: In the “Transform” tab, click “Fill” and choose the
appropriate method (e.g., “Fill Down”).
● Close and apply: Click “Close & Apply.”
Designing Reports in Power BI: A Comprehensive Guide
➢ Choose a Layout:
• Select a page layout: Choose a layout that best suits your report’s
content and purpose.
• Add pages: If your report requires multiple sections, add additional
pages.
