Utilising Data Power: The Business Analyst's Quick Guide to Power Query
By
Kenneth Gray
Power Query has emerged as a strong ally for Business Analysts (BAs) in the large ecosystem of data analysis tools. Power Query, a component of Microsoft's Power BI package, is intended to connect, clean, convert, and load data from multiple sources. But how might BAs maximise its potential?
Recognising the Value of Power Query
Data is the foundation of decision-making for Business Analysts (BA's). However, raw data, with its variations and formats, can be difficult to manage. This is where Power Query can be useful:
Data Importation: Access databases, files, internet services, and other resources.
Data Transformation: Prepare data for analysis by cleaning, filtering, reshaping, and combining it.
User-friendly Interface: BAs can work with data using a GUI-based text editor rather than going deep into complex coding.
Five Quick Steps to Power Query
1. Connecting to Data Sources:
Power Query has a wide range of connectors, ranging from Excel workbooks to SQL Server databases to web services. I have found for the best performance, use the most direct connector to your source.
2. Data Cleaning:
Take care of any missing values, mistakes, or duplication. You can use the functions in Power Query to replace errors, fill down/up, or manually correct entries.
3. Data Transformation:
Depending on your analysis needs, Data can be reshaped on Query in different ways. You can pivot and unpivot tables, separate columns by delimiter, combine data from many sources, or group entries.
4. Advanced Transformations:
If you have specialised operations, use conditional columns, date calculations, or even write custom M or R scripts.
5. Load Data:
Once the data has been processed, load it into Power Pivot or Power BI Desktop for further analysis and visualisation.
Microsoft Power Query process - Microsoft Learn
Power Query Formula Language (M)
While Power Query has an easy-to-use interface, you can achieve greater customisation with the M language. Though it is not required, a basic understanding of M language can enable you to build better personalised solutions.
Best Practises for BAs Using Power Query
Query Folding: Allow the source system to handle as much heavy lifting as possible to improve performance.
Prevent Overloading: It's tempting to pull in massive volumes of data, but limit yourself to what's relevant to the analysis.
Document Steps: Given that projects may be reopened or handed on to other BAs in the future, always document your Power Query steps.
Stay Up to Date: Microsoft's Power Query capabilities are constantly changing, so always keep a watch out for upgrades and new features.
Continuous Skill Improvement
Official Documentation: Microsoft offers free tutorials and case studies. This is how I gained most of my knowledge.
Forums and Communities: For obtaining guidance or exchanging knowledge use platforms such as Microsoft's Power BI Community or Stack Overflow.
Conclusion
Power Query is more than just a tool for Business Analysts; it uncovers stories hidden within data. BAs can raise their data preparation procedures by learning its functionalities, ensuring that their insights are based on clean, relevant, and well-structured data.
