Analytics Definitions

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  • A

    A/B testing (split testing)

    A/B testing, sometimes called split testing, is an assessment tool for identifying which version of something helps an individual or organization meet a business goal more effectively.

  • 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.

  • business analytics (BA)

    Business analytics (BA) is the iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis. Business analytics is used by companies that are committed to making data-driven decisions.

  • C

    Campbell's Law

    Campbell's Law is the observation that once a metric has been identified as a primary indicator for success, its ability to accurately measure success tends to be compromised.  

  • citizen data scientist

    A citizen data scientist is any individual who contributes to the research of a complex data initiative but who does not have a formal educational background in data analytics (DA) or business intelligence (BI).

  • collaborative BI (collaborative business intelligence)

    Collaborative BI (collaborative business intelligence) is the merging of business intelligence software with collaboration tools, including social and Web 2.0 technologies, to support improved data-driven decision making.

  • customer analytics (customer data analytics)

    Customer analytics, also called customer data analytics, is the systematic examination of a company's customer information and customer behavior to identify, attract and retain the most profitable customers.

  • customer intelligence (CI)

    Customer intelligence (CI) is information derived from customer data that an organization collects from both internal and external sources.

  • 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 journalism

    Data journalism in an approach to writing for the public in which the journalist analyzes large data sets to identify potential news stories.

  • data preparation

    Data preparation is the process of gathering, combining, structuring and organizing data so it can be analyzed as part of data visualization, analytics and machine learning applications.

  • data sampling

    Data sampling is a statistical analysis technique used to select, manipulate and analyze a representative subset of data points to identify patterns and trends in the larger data set being examined.

  • 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

    edge analytics

    Edge analytics applies algorithms to data at the point of collection in order to trigger actions and determine what should be sent back to a central data repository and what should be discarded.

  • 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.

  • F

    funnel analysis

    Funnel analysis is a way to measure and improve the performance of customer interactions in a step-wise progression from the initial customer contact to a predetermined conversion metric.

  • G

    Google Advertising ID

    Google Advertising ID is a piece of universally unique identifier code that allows mobile applications running on Android devices to identify users and gather data for the purposes of building profiles.

  • Google Analytics

    Google Analytics is a free Web analytics service that provides statistics and basic analytical tools for search engine optimization (SEO) and marketing purposes. The service is available to anyone with a Google account.

  • H

    Hadoop cluster

    A Hadoop cluster is a special type of computational cluster designed specifically for storing and analyzing huge amounts of unstructured data in a distributed computing environment. 

  • 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.

  • L

    Lambda architecture

    Lambda architecture is an approach to big data management that provides access to batch processing and near real-time processing with a hybrid approach.

  • location intelligence (LI)

    Location intelligence (LI) is a business analysis tool capability that enables companies to gather geographic- and location-related data to better understand global, regional and local business trends.

  • logistic regression

    Logistic regression is a statistical analysis method used to predict a data value based on prior observations of a data set.

  • M

    MapR

    MapR Technologies is a distributed data platform for AI and analytics provider that enables enterprises to apply data modeling to their business processes with the goal of increasing revenue, reducing costs and mitigating risks.

  • mobile location analytics (MLA)

    Mobile location analytics is a method used by retailers to track the movements of shoppers throughout their stores.

  • N

    named entity

    A named entity is a term or phrase that identifies an object from a set of other objects with similar attributes.

  • natural language processing (NLP)

    Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken.

  • 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.  

  • noisy text

    Noisy text is an electronically-stored communication that cannot be categorized properly by a text mining software program. Noisy text is often caused by an end user's excessive use of idiomatic expressions, abbreviations, chat and text acronyms or business-specific lingo.

  • P

    predictive analytics

    Predictive analytics is a form of advanced analytics that uses both new and historical data to forecast activity, behavior and trends.

  • R

    R programming language

    The R programming language is an open source scripting language for predictive analytics and data visualization.

  • revenue attribution

    Revenue attribution is the process of matching customer sales to specific advertisements in order to understand where revenue is coming from and optimize how advertising budgets are spent in the future.

  • S

    SAS Institute Inc.

    SAS Institute Inc. is a software vendor that specializes in advanced and predictive analytics applications, as well as business intelligence and data visualization tools.

  • Scala (Scalable Language)

    Scala is a software programming language that mixes object-oriented methods with functional programming capabilities. It was used to create the scalable Spark analytics engine.

  • 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.

  • social media analytics

    Social media analytics is the practice of gathering data from social media websites and analyzing that data using social media analytics tools to make business decisions.

  • 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.

  • text tagging

    Text tagging is the process of manually or automatically adding tags or annotation to various components of unstructured data as one step in the process of preparing such data for analysis.

  • U

    unstructured data

    Unstructured data is information, in many different forms, that doesn't hew to conventional data models and thus typically isn't a good fit for a mainstream relational database.

  • unstructured text

    The unstructured text collected from social media activities plays a key role in predictive analytics for the enterprise because it is a prime source for sentiment analysis to determine the general attitude of consumers toward a brand or idea.

  • V

    visual analytics

    Visual analytics is a form of inquiry in which data that provides insight into solving a problem is displayed in an interactive, graphical manner.

  • W

    Web analytics

    Web analytics is the process of analyzing the behavior of visitors to a Web site.

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