When to start automating and how to select the right tool for automated BI testing
Why test data after it enters your BI solution
There is a misconception that a visualization tool is only used to visualize data. Traditionally, all the transformations used to happen in the database or data warehouse (or anywhere else outside the BI solution) and then you used a BI tool to visualize that data. But this is not the case with modern BI tools. Today, there are so many things you can do within your business intelligence tool — including data transformation. Instead of going to the IT department, people responsible for visualizations make changes themselves.
It’s also worth noting that modern business intelligence tools (like Qlik, Power BI and Tableau) are extremely good at connecting to other data sources. We have a customer that just by looking at the automatically generated data landscape map in NodeGraph realized that only 50% of their data was actually travelling through their data warehouse. This is not a unique case.
The importance of data trust when it comes to BI adoption
Questioning your data is definitely better than blindly trusting it. However, the ideal situation involves implementing a data quality framework that will allow you to trust your data without any doubts. For this, testing is key.
Without such a framework, users often find themselves questioning their data without getting accurate and quick answers — having to spend 20-30% of their working time searching for the right data and/or validating said data. Testing can help companies achieve a single source of the truth, ensuring that business data I always fulfilling data quality requirements.
Automated alerts to help enforce data quality framework
Even when your data quality is high and business teams trust their data, your business and your data landscape is constantly evolving. This makes automated alerts crucial — ensuring that you are immediately informed if something unexpected happens in your data solution. Data Quality Manager offers automated alerts about the status of your tests via email and/or Slack.
Data and analytics governance that actually works
Once you’ve consolidated your data and analytics governance program with its policies, processes, roles and responsibilities, the challenge is to make it is easy for everyone to follow and maintain this. This means you should stay away from implementing processes that involve lots of manual work. Automation is key.
Find out more about NodeGraph’s data and analytics governance solution.
A continuous and iterative data testing framework is the only way to go
Automated data testing in BI solutions solves a long-standing and widespread problem of poor data quality, incorrect data and low data trust. But like with cleaning or documentation it’s a routine and not that exciting task.
Fixing the problem once and for all with the help of a continuous and iterative data testing framework largely supersedes sorting issue by issue in real-time without guaranteeing that they won’t return.
Find out how you can implement BI testing using NodeGraph Data Quality Manager.