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Self Service Business Intelligence (BI) is an approach to data analysis that allows business users to access and explore datasets even if they have no experience in BI or in related functions such as data mining and statistical analysis.
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Self Service Business Intelligence (BI) is an approach to data analysis that allows business users to access and explore datasets even if they have no experience in BI or in related functions such as data mining and statistical analysis. Self-service BI tools allow users to filter, organise, analyse, and visualise data without involving the organisation's BI and IT teams.
In contrast, self-service BI environments allow business analysts, executives, and other users to run queries themselves and create their own Data Visualisations, dashboards, and reports. As some of these users may not be tech-savvy, it is imperative that the user interface (UI) of the self-service analytics software is intuitive and easy to use.
With traditional BI tools and processes, the BI or IT team does the data analysis for business users. In this approach, users request new analytical queries that the BI analyst or other BI professional writes and executes for them. Similarly, users request new BI reports and dashboards, often through a requirements collection process initiated by BI staff.
Once the project is approved - which in some cases can take weeks - the BI team prepares the necessary data or, if necessary, works with the IT department to extract that data from the source system, transform and clean the data, and then load them into a repository or other data store. The BI team then creates queries to produce the required analysis results and designs dashboards or reports to display the information.
Organisations are implementing Self Service Business Analytics capabilities to help employees, from executives to frontline workers, easily derive valuable business insights from data collected in the BI system. The primary goal is to drive more informed decision making that leads to positive business outcomes, such as increased efficiency, better customer satisfaction, and higher sales and profits.
The Dual Analytics platform powers ad hoc queries, insights, and artificial intelligence
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