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Lisp (historically LISP, an abbreviation of "list processing") is a family of programming languages with a long history and a distinctive, fully parenthesized prefix notation. [3] Originally specified in the late 1950s, it is the second-oldest high-level programming language still in common use, after Fortran.
In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.
e. In computing, extract, transform, load (ETL) is a three-phase process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collated from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using ...
A data processing system is a combination of machines, people, and processes that for a set of inputs produces a defined set of outputs. The inputs and outputs are interpreted as data, facts, information etc. depending on the interpreter's relation to the system. A term commonly used synonymously with data or storage (codes) processing system ...
Stored procedure. A stored procedure (also termed prc, proc, storp, sproc, StoPro, StoredProc, StoreProc, sp, or SP) is a subroutine available to applications that access a relational database management system (RDBMS). Such procedures are stored in the database data dictionary. Uses for stored procedures include data-validation (integrated ...
The concept of data management arose in the 1980s as technology moved from sequential processing [2] (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than ...
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business.