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Published: 17 Jun 2014 Updated: 04 Jul 2023 Update History

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Business intelligence (Bi) refers to technologies, applications, and practices for collecting, integrating, analyzing, and presenting business information. Analytics refers to the use of (a) data and evidence, (b) statistical, quantitative, and qualitative analysis, (c) explanatory and predictive models, and (d) fact-based management to drive decision making.

Together, they include approaches for gathering, storing, analysing and providing access to data that helps users to gain insights and make better fact-based business decisions.

Organisations use business intelligence and analytics approaches to gain data-driven insights on anything related to business performance. It is used to understand and improve performance and to cut costs and identify new business opportunities.

Examples of BI and analytics applications include:

  • Measuring, tracking and predicting sales and financial performance
  • Budgeting, financial planning and forecasting
  • Analysing customer behaviours, buying patterns and sales trends
  • Tracking the performance of marketing campaigns
  • Optimising processes and operational performance
  • Improving delivery and supply chain effectiveness
  • Web and e-commerce analytics
  • Customer relationship management
  • Risk analysis
  • Strategic value driver analysis

The basic components of BI and analytics are gathering, storing, analysing and providing access to data:

Gathering data

Gathering data is concerned with collecting or accessing data, which can then be used to inform decision-making. A major challenge of gathering data is making sure that the relevant quality data is collected in the right way at the right time. If the data quality is not controlled at the data gathering stage then it can jeopardise the entire BI and analytics efforts that might follow – always remember the old adage - garbage in garbage out.

Storing data

Storing data is concerned with making sure the data is filed and stored in appropriate ways to ensure it can be found and used for analysis and reporting. When storing data the same basic principles apply that you would use to store physical goods – say books in a library – you are trying to find the most logical structure that will allow you to easily find and use the data.

The advantages of modern data-bases (often called data warehouses because of the large volumes of data) is that they allow multi-dimensional formats so you can store the same data under different categories – also called data marts or data-warehouse access layers. Like in the physical world, good data storage starts with the needs and requirements of the end users and a clear understanding of what they want to use the data for.

Analysing data

Providing access is concerned with giving decision makers access to the data and insights. Access is needed to perform analysis or to view the results of the analysis. The former is provided by the latest software tools that allow end-users to perform data analysis while the latter is provided through reporting, dashboard and scorecard applications.

Providing access

Providing access is concerned with giving decision makers access to the data and insights. Access is needed to perform analysis or to view the results of the analysis. The former is provided by the latest software tools that allow end-users to perform data analysis while the latter is provided through reporting, dashboard and scorecard applications.

Latest research

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Further reading on Business intelligence (BI) is available through the resources below.

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  • Update History
    17 Jun 2014 (12: 00 AM BST)
    First published
    04 Jul 2023 (12: 00 AM BST)
    Page updated with Latest research section, adding further reading on business intelligence. These additional resources provide fresh insights, case studies and perspectives on this topic. Please note that the original overview from 2014 has not undergone any review or updates.