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Data Virtualization can be treated as alternative to ETL and data warehouses. Both technologies aim to deliver data where they are needed. So, when should we use data virtualization and when ETL?

Solution performing Extract Transform Load (ETL) is a solution dedicated to physical data consolidation projects. It encompasses copying original or transformed data from selected data sources to company data warehouse (DW) or a new database. ETL tools are meant to copy large scale structured data sets combined with performing required transformation and purification.

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Virtualization can replace ETL to an extent, but is more often used as complementary or extended ETL/DW deployment. This technology allows relatively fast access to the additional data sources as a data warehouse supplementation or combination of several data warehouses into single logical entity. This technology eliminates the need for accessing each data source manually creating a single data source instead, saving time and resources of development teams. Data virtualization allows accessing data in real time or with slight delay and algorithms utilized eliminate overloading data sources with SQL queries.

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FOR COMBINING AND POWERING DATA WAREHOUSES

WHEN YOU MIGRATE DATA TO CLOUD SOLUTIONS

WHILE YOU SEARCH AND DISCOVER RELATED DATA

QUICK SUPPORT, SHARING OF COMPLETE DATA