With organizations generating data like never before, businesses around the world want to capitalize on this data and draw actionable and data-driven insights by performing Analyses using Business Intelligence tools. Analysis can be performed on any type of data. The only thing to keep in mind is to identify the right data for the kind of analysis you want to perform.
In this article, you will learn about Power BI, Python, and two methods that can help you set up a Power BI Python Integration, allowing you to seamlessly transfer/load data from Python to Power BI. Power BI Python Integration will allow you not only to set up informative dashboards & reports but also to carry out an insightful analysis.
What is Power BI?
Power BI is Software as a Service (SaaS) platform established by the Microsoft Corporation. It is a Business Intelligence tool that enables you to analyze your organizational data and create interactive and real-time Dashboards. Power BI can be installed as a desktop app, or mobile app and can be used online too. This way you can collaborate with anyone in your organization irrespective of where you are.
Power BI can be used to create reports using Power BI Reports Builder. Employees in every department can make use of Power BI and its collaborative power. Sales and Marketing teams can observe their latest campaign trends and customer conversion, Developers can embed Dashboards and Reports into applications, etc.
What are the Key Features of Power BI?
Power BI is a widely used tool that enables organizations to analyze their data and create Reports and Dashboards. Let’s look at some of its features:
1. Amazing and Interactive Visualizations
With Power BI you can create visualizations that appeal to the eye. Some of its visualizations are given below:
- Bar Charts
- Column Charts
- Line Plots
- Area Plots
- Pie Charts
- Scatter Plots
- Treemaps
- Funnel Analysis Charts, etc
2. Highly Useful Navigation Pane
Image Source: Microsoft Docs
As you can see in the image, the navigation pane in Power BI helps you to collaborate with your peers or other employees. It is dynamic and helps you easily navigate to the Dashboards or Reports you have created both for your personal use (My Workspace) or for collaboration. It also saves all the Dashboards and Reports related to a particular department in your organization in the Workspaces Column. It also helps you navigate to associated Apps, Deployed pipelines, recent work, and your starred Dashboards and Reports.
3. Functions for Analysis
Power BI houses numerously inbuilt functions called DAX functions that help analyze your data. These functions are predefined and you can find them in the Power BI functions library. Developers from Microsoft often keep adding more functions into the library from time to time.
4. Multiple Dataset Visualizations
Power BI supports data to be imported from a single data source or multiple data sources. This data can be On-premise or in the Cloud. Power BI also supports Both Structured and Unstructured data. Some data sources available supported by Power BI are Python, Oracle, Excel sheets, SQL Server, etc
5. Customizable Dashboards
You can create Dashboards using the pre-built templates or you can custom create them according to your requirement. These Dashboards can also be shared with others.
What is Python?
Python is an interpreted, high-level and general-purpose programming language. It is very easy to learn and code in. It has some amazing libraries and pre-built functions that make complex calculations and operations a piece of cake. Python is widely used in the fields of Machine Learning and Deep Learning, Data Analytics, Engineering, and Artificial Intelligence.
In this tutorial, you will need to use two Python libraries- Pandas and Matplotlib. Pandas library contains predefined functions that help you work with data. Matplotlib library contains predefined functions that help you plot various data visualizations.
What are the Key Features of Python?
The following features are responsible for Python Programming Language’s popularity today:
- Beginner Friendly: The Python Programming Language offers a hassle-free environment for developers. Its straightforward workflow is suitable for everyone and entry-level coders are drawn to it. Moreover, you can use and distribute its open-source codes for commercial purposes free of cost.
- Object-Oriented Programming Language: Python provides a platform for solving real-world problems using the Object-Oriented Approach, allowing you to implement concepts such as Encapsulation, Inheritance, Polymorphism, and so on.
- Robust Applications: Its simple syntax operates on natural human-readable language making it the go-to choice of projects on Python Programming Language, which is faster as compared to other Programming Languages. Furthermore, its versatile nature makes it the ideal choice for Web Development and Machine Learning projects.
- Large Communities: Due to Python’s immense popularity, a huge active community of programmers is available online that contributes to this language’s modules and libraries. Moreover, this vast support community is ready to help in case you or any other coder gets stuck in a programming issue. You can easily get suggestions and solutions by posting your issue on these community pages.
What is the Need for Power BI Python Integration?
Python is a powerful tool to create visualizations and Power BI is great at creating Dashboards. These Dashboards will contain multiple such visualizations that will give you a complete view of your organization’s KPIs, growth, metrics, etc. So, if you build a Power BI Python Integration, you can make use of the capabilities of both Python and Power BI.
Prerequisites
You need to make sure that you have the following software and packages installed before setting up Power BI Python Integration:
- Python
- Pandas library in Python
# type the below pip command in the command prompt to install the pandas library
pip install pandas
- Matplotlib library in Python
# type the below pip command in the command prompt to install the matplotlib library
pip install matplotlib
What are the Methods to Setup Power BI Python Integration?
You will learn two different methods that you can use to set up a Power BI Python Integration:
Method 1: Setting up Power BI Python Integration Manually
This tutorial will guide you step-by-step and help you build a Power BI Python Integration:
Step 1: Enabling Python Scripting in Power BI
Image Source: Microsoft Docs
Open your Power BI Desktop Application. Go to the drop-down File menu in the top left corner and select settings. In the settings menu go to Options. In the Detected Python home directories menu under the Options window, select Python Scripting. A Python Script options page is loaded. Here you need to specify the home directory which is the local Python installation path (path set during installation of Python). After this, click on the OK button.
Step 2: Write a Python Script
Go to your local Python IDE and write a Python Script. Make sure you are importing and using Pandas and Matplotlib libraries to create your data model and visualizations. Create data frames using Pandas to ensure that this method works. Let’s take an example script for your better understanding:
import pandas as pd
data = [['Alex',10],['Bob',12],['Clarke',13]]
df = pd.DataFrame(data,columns=['Name','Age'],dtype=float)
print (df)
Now run the above script in the local IDE to make sure that there are no errors in the code. The observed output of the above code will be:
Name Age
0 Alex 10.0
1 Bob 12.0
2 Clarke 13.0
Upon successfully running the script in the local python IDE you can move onto the next step.
Step 3: Run the Python Script in Power BI
Image Source: Microsoft Docs
To run your Python Script in Power BI, go to Home Ribbon and navigate to the Get Data menu. An Options window pops up. Now select Options from the Get Data window. Choose the Python Script option on the loaded page and click on the connect button as shown in the above image. A new Python Script window opens with an empty dialog box. Copy the code written in your local Python Script and paste it into the dialog box. The result will look similar to the below image:
Image Source: Microsoft Docs
Now, click on the OK button.
Step 4: Import Data into Power BI
After running the script, the Navigator window opens and you can load the data and use it. For the example, select df, as shown in the image, then click on Load.
Image Source: Microsoft Docs
The data is now loaded into Power BI. You have now created a Power BI Python Integration successfully. To create visualizations using Power BI Integration, refer to the official tutorial here.
What are the Drawbacks of Manual Method?
There are a lot of limitations you have to keep in mind when you use the manual Power BI Python Integration:
- Since Power BI Desktop supports only Pandas data frames, you cannot import data in any other format.
- If your Python Script runs more than 30 minutes, it times out.
- Interactive calls are not supported. If an interactive call is included in your script, it gets terminated immediately.
- Also, you cannot set a relative path to Working Directory in the Python Script, you must always specify the full path.
- In the current versions, Nested Tables are not supported.
- You also won’t be able to integrate Python into Reports that have the Enhanced Metadata Preview feature.
Method 2: Using Hevo to Set up Power BI Python Integration
Why limit yourself to just moving data using Python? In this method, you will learn about moving your data from Python or any source of your choice to a BI tool such as Power BI seamlessly! You can then create Reports and Dashboards for your data using Power BI. Hevo can help you create a Power BI Python Integration with ease.
Hevo Data, a No-code Data Pipeline helps to transfer your data from Python(among 150+ sources) to Power BI and numerous other BI tools, Data Warehouses, or destinations of your choice. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also takes care of transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
It provides a consistent & reliable solution to manage data in real-time and you always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using a BI tool of your choice such as Power BI.
Steps to use Hevo Data
Set up a Power BI Python Integration in Hevo by following 3 easy steps:
- Connect: Connect Hevo with Python and various other Databases, SaaS, Marketing, etc. data sources by simply logging in with your credentials.
- Integrate: Consolidate your data from Python and several sources in Hevo’s Managed Data Integration Platform and automatically transform it into an analysis-ready form.
- Visualize: Connect Hevo with your desired BI tool such as Power BI and visualize your unified channel & marketing data easily to gain better insights.
Check out Some of the Cool Features of Hevo:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a safe & consistent manner with zero data loss.
- 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 interactive UI, is simple for new customers to work on and perform operations.
- Robust Integration with BI tools: Hevo supports connecting with numerous BI tools such as Tableau, Looker, Power BI, etc. in a matter of minutes and lets you analyze your marketing & channel data in a completely secure and hassle-free manner in real-time.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
You can try Hevo for free by signing up for a 14-day free trial.
Conclusion
Keeping track of all your organizational data and metrics is essential for boosting growth and increasing revenue. Every metric in your Dashboard will help you understand more about your company’s progress and will allow you to make quick and accurate data-driven business decisions. In this article, you have learned about setting up Power BI Python Integration using two different methods.
Easha is a programming enthusiast with 2+ years of experience. She has worked in automation test script creation, regression testing, and integration projects like Thyrocare Integration. She has a bachelor's degree in Computer Science and loves writing technical articles about data engineering. Her goal is to help people solve everyday problems through her work.
