Power BI Desktop and Power BI Services support a large range of data sources. Click on the Get Data button, and it shows you all the available data connections. You can connect to different Flat files, Azure cloud, SQL database, and Web platforms, also such as Google Analytics, Facebook, and Salesforce objects. It includes an ODBC connection to connect to

ODBC data sources.
Here are the available data sources in Power BI, as shown below:
• SQL Database
• Flat Files
• Blank Query
• OData Feed
• Azure Cloud Platform
• Online Services
• Oracle database
• IBM Db2 database
• IBM Netezza
• IBM Informix database (Beta)
• Other data sources such as Exchange, Hadoop, or active directory
To connect data in Power BI Desktop, you need to click on the Get Data button within the main screen. First, it shows you the most common data sources. Then click on the More option to see a full available list of the data sources.

On the left side, it shows a category of all the available data sources. You also have an option to perform search operation at the top.
Let’s see all the listed data sources in detail:
1. All
In this category, you can see all the available data sources of the Power BI desktop.
2. File
When you click on the File option, it shows you all the flat files supported in Power BI desktop. Select any file type from the list and click on the Connect button to connect that file.

3. Database
When you click on the Database option, it shows you the list of all the database connections that you can connect to any database.

You need to pass the server name, user name, and password to connect. Also, you can connect via a direct SQL query using the Advanced option. You can also select connectivity mode – Import or DirectQuery.
Import: Import method allows to perform data transformations and manipulation. When you publish the data to PBI service (limit 1 GB), it consumes and pushes data into Power BI Azure backend and data can be refreshed up to 8 times a day and a schedule can be set up for data refresh.
DirectQuery: It limits the option of data manipulation, and the data stays within the SQL database. The DirectQuery is live, and there is no need to schedule refresh as within the Import method.

4. Azure
Using the Azure option, you can connect with the database within the Azure cloud. Below screenshot shows you the varied options available under the Azure category.

5. Online Services
The Power BI also allows you to connect to different online services such as Exchange, Salesforce, Google Analytics, and Facebook.
Following screenshots showed the varied options available under Online Services.

6. Other
Below screenshot shows the varied options available under other categories.

So, this brings us to the end of blog. This Tecklearn ‘Power BI Data Sources and How to connect with them’ blog helps you with commonly asked questions if you are looking out for a job in Power BI. If you wish to learn Power BI and build a career in Business Intelligence domain, then check out our interactive, Microsoft Power BI Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

Microsoft Power BI Training

Microsoft Power BI Training

About the Course

Microsoft Power BI Training at Tecklearn will help you achieve expertise in business analytics Our best online training course teaches you all important concepts like Power BI Desktop, Mobile, Power Query & Power Pivot, Data modelling, visualization, creating dashboards and reports, DAX, etc. As part of this program, you will work on real-world projects. Also, our Power BI course curriculum will equip you with all the key skills that are required to clear the Microsoft Power BI Certification exam (70-778).

Why Should you take Microsoft Power BI Training?

• The average annual pay for a Power BI Professional is $114,000 . -PayScale.com.
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What you will Learn in this Course?

Introduction to Microsoft Power BI

• Microsoft Power BI Introduction
• Power BI Products
• Power BI Architecture
• Installing Power BI
• Connecting to Data Sources

Power BI Workflow

• Key features of Power BI workflow
• Power BI Vs MSBI
• History of Power BI
• Power BI Products
• Data modelling and relationships

Power Query for Data Transformation

• Power Query for Data Transformation
• Learning about Power Query for self-service ETL functionalities
• Working with Excel data
• Introduction to Query Editor
• Data transformation
• Pivot and UnPivot
• Merge Join, relational operators, date, time calculations, working with M functions
• Summary Tables
• Writing custom functions and error handling
• M advanced data transformations

Filters and Drill Down Report

• Visualization Filter
• Page Level Filter
• Report LEVEL Filter
• DRILL Through Filter or Report
• BookMark Report

Power Pivot for Data Modelling

• What is SSAS
• Data Modelling
• Star Schema
• Snowflake Schema
• Introduction to MDDB and Tabular
• Data Access Modes
• Tabular with DAX
• Power BI with DAX
• DAX Functions

Data Analysis Expression – DAX Queries

• TABULAR with DAX
• Power BI with DAX
• Calculated Members, Row, Filter & Evaluation Context
• Cumulative Charts
• Calculated Tables, ranking and rank over groups
• DAX advanced features

Power BI Desktop & Administration

• Reports and Visualization
• Learning about data modelling and data relationships
• Deploying data gateways
• Reports and Dashboards
• On Premises Data Gateway
• Gateway Clusters

Introduction to Power Q & A

• Power Service
• Power Q & A best practices
• Integrating with SaaS applications
• Gateway

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