Data mining Definitions

  • A

    Ad Hoc Analysis

    Ad hoc analysis is a business intelligence (BI) process designed to answer a single, specific business question.

  • advanced analytics

    Advanced analytics is a broad category of inquiry that can be used to help drive changes and improvements in business practices.

  • association rules (in data mining)

    Association rules are if-then statements that help to show the probability of relationships between data items within large data sets in various types of databases.

  • B

    big data analytics

    Big data analytics is the often complex process of examining large and varied data sets -- or big data -- to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions.

  • D

    data artist

    A data artist is a business analytics (BA) specialist who creates graphs, charts, infographics and other visual tools that help people understand complex data.

  • data exploration

    Data exploration should be the first step in any data analysis. Its purpose is to familiarize analysts with the features of the dataset with which they are working.

  • data science as a service (DSaaS)

    Data science as a service (DSaaS) is a form of outsourcing that involves the delivery of information gleaned from advanced analytics applications run by data scientists at an outside company to corporate clients for their business use.

  • decision-making process

    The decision-making process, in a business context, is a set of steps taken by managers in an enterprise to determine the planned path for business initiatives and to set specific actions in motion.

  • deep analytics

    Deep analytics is the application of sophisticated data processing techniques to yield information from large and typically multi-source data sets comprised of both unstructured and semi-structured data.

  • E

    ensemble modeling

    Ensemble modeling is the process of running two or more related but different analytical models and then synthesizing the results into a single score or spread in order to improve the accuracy of predictive analytics and data mining applications.

  • I

    in-memory analytics

    In-memory analytics queries data residing in a computer’s random access memory (RAM) rather than data stored on physical disks. This results in vastly shortened query response times.

  • N

    noisy data

    Noisy data is meaningless data. The term was often used as a synonym for corrupt data, but its meaning has expanded to include data from unstructured text that cannot be understood by machines.  

  • O

    opinion mining (sentiment mining)

    Opinion mining is a process for tracking the mood of the public about a certain product, for example, by building a system to examine the conversations happening around it.

  • S

    social analysis

    Social analysis is the practice of analyzing a situation or social problem through objective, systematic exploration.

  • T

    text mining (text analytics)

    Text mining is the process of exploring and analyzing large amounts of unstructured text data aided by software that can identify concepts, patterns, topics, keywords and other attributes in the data.

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