Data Warehouse Testing Services We Offer
ETL Testing

ETL Testing

If ETL does not work as expected, data will be corrupted, inadequately altered, or lost in transit, leading to inaccurate conclusions and erroneous business decisions. By performing this testing, our qualified experts check the correctness of ETL using a data-centric approach: they examine the data at each entry point, identify duplicates and missing foreign keys, check that the transformations comply with your business rules and the consistency of the source and target data. With a wide variety or amount of data stored in DWH, our experts offer automated ETL testing of your DWH using iCEDQ, QuerySurge and other tools.

BI Testing

BI Testing

In order to make informed business decisions, data quality must be maintained at all stages, so we ensure that OLAP operations are working properly and compare the data and its format in DWH to ensure that it provides accurate information. We also check the display times of your reports to make sure they meet your requirements. BI testing ensures the reliability of the data and the accuracy of the conclusions drawn from the BI process. We also test the performance of BI projects by stress testing reports and business intelligence dashboards to verify that a new report or dashboard meets requirements.

Security Testing

Security Testing

Data warehouses contain sensitive business information such as personal data of customers and employees or financial information from the internal environment of the company and external partner environment that requires enhanced protection. DWH security testing will ensure the correctness of access at different authorization levels and will help to establish the work of the encryption and decryption of data adopted for your business: your business data will befully protected in accordance with the required security measures, and, if necessary, all data backup operations will work as expected.

Data Warehouse Testing Platforms
Tools We Use for Data Warehouse Testing
Solutions For Which We Implement Data Warehouse Testing
DW Apps

BI Apps

Our Approach to Data Warehouse Testing

01
Analysing project requirements

02
Data source validation

03
Test design

04
Source system data extraction

05
Test execution

06
Test summary report

F.A.Q
What is DWH testing?

Data warehouse testing is a method of examining data in a warehouse in which it is tested for integrity, accuracy, consistency, and reliability to fit the data structure of a company. The main goal of data warehouse testing is to ensure that the data integrated into the data warehouse is reliable enough for the company to make decisions. Data warehouse testing is a combination of BI testing and ETL testing.

ETL tool is used to extract data from various data sources, transform data and load it into DW system; however, the BI tool is used to create interactive and ad-hoc reports for end users, dashboards for senior management, data visualizations for monthly, quarterly and annual board meetings.

Data warehouse is a specially organized array of enterprise data processed and stored in a single hardware and software complex, which provides quick access to operational and historical information, multidimensional data analysis (KPI for various dimensions), obtaining forecasts and statistics in terms of agreed reference information.

Companies use different reporting tools in the context of the data warehouse so that everyone can analyze the data for decision making and reporting. Therefore, to ensure that the right decisions are made, you need to be sure that all data in the data warehouse is written correctly and has no errors. To achieve this, companies need to fully test their data warehouse.

What is the difference between ETL testing and data warehouse testing?

ETL testing and database testing both involve data validation, but they are not the same. ETL testing is usually performed on data in a data warehouse system, whereas database testing is usually performed on transactional systems where data flows from different applications into a transactional database.

In general, ETL testing is part of DWH testing. The data warehouse is built using data extraction, transformation and loading procedures. ETL processes extract data from sources, transform it to meet BI reporting requirements, and then load it into the target data warehouse.

Database testing focuses on data accuracy, data validity, and valid values. It includes the following operations:

  1. Checking if primary and foreign keys are supported.
  2. Checking the correctness of column values in the table.
  3. Checking the accuracy of data in columns.
  4. Checking for missing data in columns.

Common database testing tools include Selenium, QTP, etc.

A typical ETL-based data warehouse uses staging area, data integration, and access layers to perform its functions. This is usually a three-layer architecture:

  1. Intermediate level. A staging layer or staging database is used to store data retrieved from various source data systems.
  2. Data integration layer. The integration layer transforms data from the staging layer and moves the data into the database, where the data is organized into hierarchical groups, often called dimensions, into facts and facts are aggregated. The combination of fact tables and dimensions in the DW system is called a schema.
  3. Access level. The access layer is used by end users to obtain data for analytical reports and information.

ETL testing is performed before the data is moved to the production data warehouse system. It is sometimes also called table balancing or production reconciliation. It differs from database testing in terms of its scope and the steps you need to take to complete it.

The main purpose of ETL testing is to identify and correct data defects and common errors that occur before data is processed for analytical reporting. However, there can be problems when testing ETL:

  1. Loss of data in the ETL process.
  2. Invalid, incomplete, or duplicate data.
  3. The DW system contains historical data, so the amount of data is too large and extremely difficult to perform ETL testing on the target system.
  4. ETL testers usually do not have access to view the timelines in the ETL tool. They have little or no access to BI reporting tools to see the final layout of reports and data within reports.
  5. It is difficult to generate and create test cases as the amount of data is too large and complex.
  6. ETL testers are usually unaware of the end-user reporting requirements and business flow of information.
  7. ETL testing includes various complex SQL concepts for validating data on a target system.
  8. Sometimes testers are not provided with source-to-target matching information.
  9. An unstable testing environment delays the development and testing of the process.
How many testers are required in a DWH testing project?

It all depends on the complexity of the data warehouse QA procedure. The number of required testers is formed during the drafting of the test plan.

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