Testing in Data warehouse Last Updated : 07 Jul, 2020 Comments Improve Suggest changes Like Article Like Report Data Warehouse stores huge amount of data, which is typically collected from multiple heterogeneous source like files, DBMS, etc to produce statistical result that help in decision making. Testing is very important for data warehouse systems for data validation and to make them work correctly and efficiently. There are three basic levels of testing performed on data warehouse which are as follows : Unit Testing - This type of testing is being performed at the developer's end. In unit testing, each unit/component of modules is separately tested. Each modules of the whole data warehouse, i.e. program, SQL Script, procedure,, Unix shell is validated and tested. Integration Testing - In this type of testing the various individual units/ modules of the application are brought together or combined and then tested against the number of inputs. It is performed to detect the fault in integrated modules and to test whether the various components are performing well after integration. System Testing - System testing is the form of testing that validates and tests the whole data warehouse application. This type of testing is being performed by technical testing team. This test is conducted after developer's team performs unit testing and the main purpose of this testing is to check whether the entire system is working altogether or not. Challenges of data warehouse testing are : Data selection from multiple source and analysis that follows pose great challenge. Volume and complexity of the data, certain testing strategies are time consuming. ETL testing requires hive SQL skills, thus it pose challenges for tester who have limited SQL skills. Redundant data in a data warehouse. Inconsistent and inaccurate reports. ETL testing is performed in five stages : Identifying data sources and requirements. Data acquisition. Implement business logic's and dimensional modeling. Build and populate data. Build reports. Comment More infoAdvertise with us Next Article Testing in Data warehouse S Shivamthakur77 Follow Improve Article Tags : DBMS Software Engineering Software Testing Similar Reads Types of Data Warehouses A data warehouse is a centralized repository that allows you to store large volumes of structured and unstructured data from multiple sources. Data warehouses are essential for data analysis, business intelligence, and reporting. Understanding the different types of data warehouses can help organiza 13 min read ETL Process in Data Warehouse The ETL (Extract, Transform, Load) process plays an important role in data warehousing by ensuring seamless integration and preparation of data for analysis. This method involves extracting data from multiple sources, transforming it into a uniform format, and loading it into a centralized data ware 7 min read Data Mining: Data Warehouse Process INTRODUCTION: Data warehousing and data mining are closely related processes that are used to extract valuable insights from large amounts of data. The data warehouse process is a multi-step process that involves the following steps: Data Extraction: The first step in the data warehouse process is t 8 min read Building a Data Warehouse in DBMS A Data warehouse is a heterogeneous collection of different data sources organized under unified schema. Builders should take a broad view of the anticipated use of the warehouse while constructing a data warehouse. During the design phase, there is no way to anticipate all possible queries or analy 5 min read What is a Data Staging Area in data warehouse? Anytime you have multi-tasked or used data from one source and then from another, you have come across this. Welcome to the Data Staging Area (DSA), a behind-the-scenes member of the data warehousing fraternity whose only job is to clean up the guests and ensure everyone is on the same page before t 15+ min read Like