How data integration experts work to integrate data ready for advance analysis
Data preparation typically involves data selection from different sources. Integration from different sources is a critical time-consuming step. Data are rarely centrally available, summarized, and/or ready to be consumed in advanced analytical tasks.
Data integration involves combining data residing in different sources and providing users with a unified view of these data.1 This process becomes significant in a variety of situations. For instance, megaresorts must pull data from their casinos, retail, restaurants, golf course, hotel, and so on to conduct effective marketing campaigns.
A concept that appears as a result of bringing data from different resources is the need to transform the data in such a way that they are intelligible when put together in a data warehouse, for example. Metadata are data about the data. In simple words, metadata are a dictionary of the data contained in a particular system, complete with definitions and transformations among other characteristics.
A data transformation converts a set of data values from the data format of a source data system into the data format of a destination data system.
Data transformation for system needs can be divided into two steps: data mapping and extract, transform, and load (ETL) code generation. In addition, ...
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