BI/Report Testing 

As part making data fit for purpose and use, rules (business as well technical) are applied to raw data, which is acquired from various sources systems. This enriched information is delivered in the form of dashboards and is available for the business executives to make the right decisions. So, it is significantly important to make sure these numbers once published are complete, accurate and trustworthy.

Data engineers, quality assurance engineers and analysts should be in a good position to answer the big business questions - “Are these reports reflecting the numbers correctly?” Information in reports can go wrong for a variety of reasons. For example - Let's say an upstream source system that feeds the customer information had gone down due to infrastructure related issues overnight and the pertinent ETL process failed to capture newer changes since the last successful run into the data warehouse. It's essential for the report development teams be aware of this in advance so that they are able to take appropriate steps including notifying business stakeholders of report issues and in the meantime working with the source system and the data engineering teams to resolve data latency issues.

Data-driven insights thru Business intelligence (BI) are crucial in many industries, given there are so much of reporting that occurs, a need for bringing efficiency thru automated testing these reports is growing in popularity. Testing software help businesses automatically validate and reconcile huge volumes of data faster so to mitigate the risk of not discovering serious issues with data on a timely basis, and help organizations make informed decisions by providing new market insights quicker.

The traditional manual approach of BI/Report testing has several flaws, and it takes a lot of time in identifying and fixing the issue. Typically the numbers in the dashboard are compressed and rolled up at a very high level to enable speed of report processing and rendering.

So, taking a number from the dashboard at a very high level of granularity reconciling against raw data from the database table(s) which could be in millions and billions of records at a lowest granular level is a very complex and tedious operation.

RDt (the low-code no-code data quality automation tool) has all the capability to connect to any of the analytical tools like PowerBI, Tableau, Looker, SAP Bex Analyser, SAP Business Objects reports, Cognos Analytics, etc. and can test/validate/reconcile the published data against the source data at any phase of its extract, transform, load (ETL) processes. Basically, RDt can read the data behind the graphs and can use that data to compare against the source data, and this complex verification process can be built leveraging its proprietary low-code , no-code Scenario Builder.

These scenarios can be orchestrated and automated via a built-in batch scheduler, and the exceptions or anomalies can be informed to the target audience automatically via emails and thru tickets generated within in Jira and Servicenow. This data observability capability proactively alerts and aids teams in quickly identifying the root cause of the issue before business submits high-priority incidents.

RightData is a software product development company providing low-code, no-code solutions with optimal features and quick turnaround. We can help you meet your data analytics goals through our technology solutions. Our tools can improve value creation from your datasets so that you can make accurate, trustworthy, timely, low-cost decisions for your company. RightData will support you at every phase of your data analytics journey.