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

    BABOK Guide (Guide to the Business Analysis Body of Knowledge)

    The guide to the Business Analysis Body of Knowledge, or the BABOK Guide, is a book from the International Institute of Business Analysis (IIBA) that provides essential support and direction to business analysts (BAs) by presenting a collection of the activities that comprise business analysis.

  • big data analytics

    Big data analytics is the often complex process of examining large and varied data sets, or big data, to uncover information -- such as 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 is the first step in data analysis and typically involves summarizing the main characteristics of a data set, including its size, accuracy, initial patterns in the data and other attributes.

  • 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.  

  • S

    sentiment analysis (opinion mining)

    Sentiment analysis, also referred to as opinion mining, is an approach to natural language processing (NLP) that identifies the emotional tone behind a body of text.

  • social analysis

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

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