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Endigest AI Core Summary
This guide covers the state of Business Intelligence analytics in the AI era, explaining why traditional BI still falls short and what modern data intelligence offers.
•Only ~50% of business users are satisfied with data access, revealing a persistent gap between data collected and insights acted upon
•Traditional BI evolved from static dashboards (IBM Cognos, BusinessObjects) through self-service discovery tools (Tableau, Qlik) to search-driven natural language interfaces
•BI analysts work across data collection, preparation, statistical analysis, visualization, and increasingly require familiarity with machine learning and predictive analytics
•The four types of analytics — descriptive, diagnostic, predictive, and prescriptive — represent a maturity progression most organizations move through sequentially
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Three core failures of traditional BI are rigidity (can't follow chains of inquiry), expert bottleneck (2–3 week turnaround for new reports), and dashboard overload (fragmente
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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