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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  3. Business intelligence - Wikipedia

    en.wikipedia.org/wiki/Business_intelligence

    Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. [1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text ...

  4. Looker (company) - Wikipedia

    en.wikipedia.org/wiki/Looker_(company)

    Looker Data Sciences, Inc. is an American computer software company headquartered in Santa Cruz, California. It was acquired by Google in 2019 and is now part of the Google Cloud Platform . Looker markets a data exploration and discovery business intelligence platform.

  5. 15 Biggest Data Mining Companies in the World - AOL

    www.aol.com/news/15-biggest-data-mining...

    For more companies, head on over to 5 Biggest Data Mining Companies in the World. Data mining is one of the most important industries today, particularly when it comes to corporate functioning.

  6. Industry analyst - Wikipedia

    en.wikipedia.org/wiki/Industry_analyst

    The IIAR provides this official definition: [1] An information and communications technology (ICT) industry analyst is a person, working individually or within a firm, whose business model incorporates creating and publishing research about, and advising on how, why and where ICT-related products and services can be procured, deployed and used.

  7. Business analytics - Wikipedia

    en.wikipedia.org/wiki/Business_analytics

    The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available. [ 3 ] Previously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year.