iceDQ for BI Report Testing & Dashboard Testing
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The document discusses the importance of business intelligence (BI) report testing in ensuring the accuracy and reliability of BI reports, dashboards, and the data pipeline. It outlines different stages of data processing, techniques for automating BI testing, and emphasizes the need for organizations to validate their reports to avoid compliance issues and improve decision-making credibility. The text highlights IcedQ's capabilities in automating BI testing to guarantee data quality and support effective business intelligence operations.
iceDQ for BI Report Testing & Dashboard Testing
- 1. Netezza to Snowflake Migration- Case Study iceDQ.ai | contact@icedq.ai | 203 666 4442 | USA BI Report Testing
- 2. Author : Sandesh Gawande CTO - iceDQ Linkedin : https://www.linkedin.com/in/sandeshgawande/ 2
- 3. 3 What is BI Report Testing? And The Importance of BI Testing
- 4. 4 What is BI Report Testing? • Business Intelligence Testing helps business users to Test, Validate & Verify the accuracy of the BI Reports , the Dashboards ,the Data Layer and its Metadata. • The principle for BI testing is very simple. What you do vs what you expect. The Delta defines the magnitude of the failure. • Business Users needs to ensure that the BI Reports are delivered correctly. But BI reports are just a final output of a very long data pipeline. • If the report is wrong, it is not necessary that the defect is in the report; the root cause of the defect might be somewhere along the breadth of the data pipeline. ? BI Report Accuracy? BI Report Business User
- 5. 5 Importance BI Report Testing • BI Testing not only helps to achieve trustworthy decision support system (DSS) but also certifies your BI Reports and hence improves the credibility of your business. • Inaccurate BI Reports affects organization’s credibility and exposes them to compliance and legal issues. It can also lead to hefty fines. • Organizations therefore cannot afford to ignore BI testing 100% ACCURACY GUARANTEE Business End User Business Analyst Data Steward
- 6. 6 The Data Pipeline The data pipeline can be divided two distinct stages: • Data Processing & Storage. • BI Testing. Source Data Data Warehouse Front End Meta Data Reports Dashboard ETL Part A : Data Processing & Storage Part B : BI System
- 7. 7 Part A : Data Processing & Storage Here are examples to know why Part A needs to be tested • Source Data: Sales number could be populated as 1000 instead of 100 and the defect in data can propagate downstream to reports. • ETL: A file might be accidentally loaded twice or say customer data is integrated incorrectly because the names are not an exact match • Database/Data Warehouse: It is possible that some orders were missed in the data warehouse thus giving shipment data without the orders. Source Data Data Warehouse ETL Part A : Data Processing & Storage
- 8. 8 Part B : BI Testing Here are examples to know why Part B needs to be tested • Data Layer: Business users needs to verify different sales revenue dimensions against its source data. • BI Report: BI Reports accuracy should be tested against the data warehouse. • Dashboards: Regression testing for a collection of multiple reports to achieve 100% decision accuracy. Front End Meta Data Reports Dashboard Part B : BI System
- 9. 9 How to Automate BI Testing? • The report can be tested if access is available to the data set in a report or prompts are avail- able in programmatic fashion. • Assuming that is true, let’s look at some of the techniques. The actual results are in reports, here we assume that the specific result is available to us programmatically. • Now the question arises on expected data. if the expected data is not known or is only in the business users mind, we cannot automate results. • But if he/she (developers) writes down the ex- pected result or points to a location where we can find it then we can automate the testing with iceDQ. Report Reconciliation Report Validation 100% ACCURACY GUARANTEE
- 10. 10 Core Component of BI testing The three-core component of BI testing are: • Data Layer/ Metadata • BI Reports • BI Dashboards Item Code PQ279 117,024 198,870 36,036 PQ280 PQ281 Sales Revenue Cust Code Dimension CU001 117,024 123,273 154,039 CU002 CU003 Sales Revenue City Austin 74,618 174,619 102,693 Florence pflugerville Sales Revenue Data Layer
- 11. 11 Data Layer Testing Technique • With this technique, the business user can easily compare the data from the data layer with the equivalent database. • Here sales revenue column is a measure as it has numerical data, whereas year or quarter are dimensions. • Data Layer Testing focuses on reconciliation of all these dimensions and measures with the source data. Item Code PQ279 117,024 198,870 36,036 PQ280 PQ281 Sales Revenue Cust Code Dimension CU001 117,024 123,273 154,039 CU002 CU003 Sales Revenue City Austin 74,618 174,619 102,693 Florence pflugerville Sales Revenue Data Layer Database Order No 8180 PQ279 PQ280 PQ281 PQ281 PQ279 PQ279 PQ280 PQ280 CU001 CU001 CU001 CU003 CU002 CU003 CU002 CU003 Austin Austin Austin Pflugerville Florence Florence Florence Pflugerville 1 1 1 2 1 2 1 2 30,578 25,500 18,540 17,496 35,100 51,346 88,173 85,197 8180 8180 8181 8181 8182 8182 8182 Item Code Cust Code City Month Sales Revenue
- 12. 12 BI Report Testing Technique • Say you have a BI report present in two different environments and the business user needs to be sure that both the reports must have exactly the same metrics. • For example, sales revenue for the first two quarters in the year 2014 & 2015 should be the same at both locations. • This type of BI report testing can be done by BI Testing Automation. The latest release of iceDQ for BI Testing provides excellent features for the same. 0 Q1 2014 Q2 BI Report Testing Sales 50000 100000 150000 2000000 2500000 197891 263162 154039 240205 50000000 2015 0 Q1 2014 Q2 Sales 50000 100000 150000 2000000 2500000 197891 263162 154039 240205 50000000 2015 BI Report BI Report
- 13. 13 BI Dashboard Testing Technique • A BI dashboard is essentially a collection of multiple reports that provides at-a-glance views of KPIs (key performance indicators) and progress report or reports relevant to a business process. • All such business rules can be validated with regression pack testing.
- 14. 14 Conclusion • There are many BI reporting tools in the market. Business relies on them to make critical decisions. • iceDQ helps business to automate BI testing for ensuring the quality of the BI Reports and in turn quality of the decisions. • All in all, BI testing will not only empower your business intelligence system but also your business. Read here to know more about BI Report Testing and Importance of BI Testing. Correct Decision Making Accurate BI Reports BI Testing BI Report & Dashboard Data Warehouse Data Source
- 15. About iceDQ iceDQ Use Cases Contact us 60 Long Ridge Road, Suite 303, Stamford CT 06902 | contact@icedq.ai | +1 (203)666-4442 Source Data ETL Target Data Data Monitoring Data Observability iceDQ empowers organizations to ensure data trust and reliability throughout the data life cycle. Our comprehensive platform combines data testing, data monitoring, and data observability into a single solution, enabling data engineers to proactively manage data quality and eliminate data issues before they impact business decisions. Leading companies across industries, including prominent players in banking, insurance, and healthcare, rely on iceDQ to continuously test, monitor, and observe their data-driven systems. This ensures trustworthy data that fuels informed decision-making and drives business success. Data Testing ETL & Data Warehouse Testing Cloud Data Migration Testing BI Report Testing Big Data Lake Testing System Migration Testing