A Brief History of Data Integration Sample Clauses

A Brief History of Data Integration. Combining heterogeneous data sources (information silos) has been studied since the early 1980s, with a data warehousing approach: the objective is to create a single view schema to makes different sources compatible. The data warehouse approach has the advantage to provide a fast and simple architecture because the data are already physically stored in a single queryable repository, so it usually takes little time to resolve queries (Xxxxxxx; Widom). When datasets are frequently updated, the extract, transform, load (ETL) process needs to be continuously executed for synchronization, and thus this approach becomes often unfeasible. An alternative to data warehousing, to answer to this problem have been to provide a unified query-interface to access real time data over a mediated schema, retrieving information directly from the original databases.This approach is based on schema matching, and in corresponding query transformation. An important problem that arises when considering schema matching is the resolution of the semantic conflicts between data sources (Xxxxxxx, Hema, and Xxxxxxxxxxxx). A common problem in data integration is data isolation. An important way to avoid data isolation is to enriching the information with structural metadata (data entities). This makes data integration easier. Currently, data hub, data vault and data lake approaches have surpassed on interest than structured Enterprise Data Warehouses (Xxxxxxxxxx and Xxxxx; Xxxxx). These techniques combine data of various kind into a unique location, without the need of a complex relational schema to structure the data, allowing for an agile development.
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