Project Summary

Power BI Reports & DevOps Component Improves Data Quality

Power BI Reports & DevOps Component Improves Data Quality

A major Canadian University had been experiencing issues with discrepancies in their data reports. They had an existing data warehouse across the entire organization, but the data quality was poor and inaccurate. Therefore, they were in need of a solution that could provide overall improved data quality. The client had expressed their desire to keep the data warehouse currently in place. We determined that data collected and presented in Power BI reports would satisfy the client’s data needs.  

What We Did: Power BI 

We started by doing work in Power BI that allowed the reports to match up with their evaluation criteria, which involved working heavily in SQL. We then refactored objects they had and shaped the data in the warehouse so Power BI could report on it correctly. For this client, their HR data was identified as needing to be shaped.  

These effective Power BI reports could now be validated and address data quality concerns. Additionally, we performed work in the data warehouse to push the right information out in the correct structures while simultaneously creating reports in Power BI.  

What We Did: DevOps 

The old vendor had somewhat incomplete DevOps components to deploy in the data factory. However, there was no control or deployment over the data warehouse itself. We brought in automated source control for the data warehouse and implemented automated deployments of the warehouse and data factory together.  

The client now has the option to perform controls and automated releases to independent environments to both beta and QA (testing environment and production environment). It is easy to deploy the code to the right place, at the right time.  

Why It Was Helpful 

Data inaccuracies present many challenges for an organization. These include (but aren’t limited to): 

  1. Financial losses 
  1. Missed opportunities  
  1. Poor operational efficiency 
  1. Poor data flow  
  1. Inaccurate analytics  

With Imaginet’s solution, we brought the data accuracy to within 1% of what the client wanted.  

The Challenge 

This project presented a unique challenge – the client expressed their desire to keep their existing data warehouse. Therefore, we had to work within tight parameters to provide the client with what they wanted. 

Our team has been working hard these last few months, and we are excited to share our success with you. Don’t forget to subscribe to our newsletter to stay updated on our most recent Microsoft 365 projects. Fill out the form at the bottom of the page if your data is unreliable, you desire a centralized data repository, or your data is difficult to manage.  

Technologies Used

Power BI Reports

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