Data Management/Data Warehousing Definitions

This glossary explains the meaning of key words and phrases that information technology (IT) and business professionals use when discussing data management and related software products. You can find additional definitions by visiting WhatIs.com or using the search box below.

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  • R

    RFM analysis (recency, frequency, monetary)

    RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns.

  • S

    schema

    In computer programming, a schema (pronounced SKEE-mah) is the organization or structure for a database, while in artificial intelligence (AI), a schema is a formal expression of an inference rule.

  • semantic technology

    Semantic technology is a set of methods and tools that provide advanced means for categorizing and processing data, as well as for discovering relationships within varied data sets.

  • serverless database

    A serverless database is a type of cloud database that is fully managed for an organization by a cloud service provider and runs on demand as needed to support applications.

  • snowflaking (snowflake schema)

    In data warehousing, snowflaking is a form of dimensional modeling in which dimensions are stored in multiple related dimension tables.

  • spatial data

    Spatial data is any type of data that directly or indirectly references a specific geographical area or location.

  • SQL Server Reporting Services (SSRS)

    SQL Server Reporting Services (SSRS) is a SQL Server subsystem that enables the creation of graphical, mobile and printed reports using SQL Server and other data sources.

  • star schema

    A star schema is a database organizational structure optimized for use in a data warehouse or business intelligence that uses a single large fact table to store transactional or measured data, and one or more smaller dimensional tables that store attributes about the data.

  • stream processing

    Stream processing is a data management technique that involves ingesting a continuous data stream to quickly analyze, filter, transform or enhance the data in real time.

  • Structured Query Language (SQL)

    Structured Query Language (SQL) is a standardized programming language that is used to manage relational databases and perform various operations on the data in them.

  • T

    T-SQL (Transact-SQL)

    T-SQL (Transact-SQL) is a set of programming extensions from Sybase and Microsoft that add several features to the Structured Query Language (SQL), including transaction control, exception and error handling, row processing and declared variables.

  • TensorFlow

    TensorFlow is an open source framework developed by Google researchers to run machine learning, deep learning and other statistical and predictive analytics workloads.

  • transcription error

    A transcription error is a type of data entry error commonly made by human operators or by optical character recognition (OCR) programs.

  • tree structure

    A tree data structure is an algorithm for placing and locating files (called records or keys) in a database.

  • U

    U-SQL

    U-SQL is a Microsoft query language that combines a declarative SQL-like syntax with C# programming, enabling it to be used to process both structured and unstructured data in big data environments.

  • V

    What is a vector database?

    A vector database is a type of database technology that's used to store, manage and search vector embeddings, numerical representations of unstructured data that are also referred to simply as vectors.

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