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A data warehouse has multiple functional areas whereby a centralized organizational unit is responsible for implementing it. On the contrary, data marts focus on particular functional areas hence are simple forms of a data warehouse.
A data warehouse differs from OLTP in that the former handles many large and complex queries regarding various rows of a table while the latter retrieves data from single rows. At the same time, a data warehouse is not real time and supports few users at a time compared to OLTP that can support many concurrent users.
ETL stands for Extract-Transform-Load and it is a process of how data is loaded from the source system to the data warehouse. Data is extracted from an OLTP database, transformed to match the data warehouse schema and loaded into the data warehouse database.Many data warehouses also incorporate data from non-OLTP systems such as text files, legacy systems and spreadsheets. Conventional testing is a sort of testing in which the test engineers will check the developed application or its related parts are working accordingly to the expectations of customer or not, from coding phase of SDLC to the end
difference between Data Mining and OLAP
Data marts are combined into a data warehouse cannot be built alone without considering data marts. Both has equal importance to built proper data warehouse.