Big data terms

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  • ETL (extract, transform, and load)

ETL enables companies to take data from one database and move it to another database.

ETL is accomplished by extracting data from the database that it originally is kept in, transforming the data into a format that can be used in the database that the data is being moved to, and then loading the transformed data into the database it is being moved to. The ETL process enables companies to move data in and out of different data storage areas to create new combinations of data for analytics queries and reports.

  • Hadoop

Administered by the Apache Software Foundation, Hadoop is a batch processing software framework that enables the distributed processing of large data sets across clusters of computers.

  • HANA

A software/hardware in-memory computing platform from SAP designed to process high-volume transactions and real-time analytics.

  • Legacy system

An established computer system, application, or technology that continues to be used because of the value it provides to the enterprise.

  • Map/reduce

A big data batch processing framework that breaks up a data analysis problem into pieces that are then mapped and distributed across multiple computers on the same network or cluster, or across a grid of disparate and possibly geographically separated systems. The data analytics performed on this data are then collected and combined into a distilled or “reduced" report.

  • System of record (SOR) data

Data that is typically found in fixed record lengths, with at least one field in the data record serving as a data key or access field. System of records data makes up company transaction files, such as orders that are entered, parts that are shipped, bills that are sent, and records of customer names and addresses.



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