Overview:
Descriptive analysis is the first and most essential step in analytics: it summarizes historical data to answer “what happened?” Before forecasting or predictive modeling, decision-makers need clear, reliable summaries of performance, trends, and patterns.
Why you should Attend:
- If your reports only show numbers, stakeholders still ask "so what?"-learn to summarize with meaning
- Inconsistent KPIs and wrong averages can lead to bad decisions and credibility loss
- Manual summarization is slow-learn a structured approach using a real case study
- Without descriptive analysis, trends, outliers, and data quality issues stay hidden
- Build confidence to communicate insights clearly in reviews and business meetings
Areas Covered in the Session:
- Descriptive Analysis Fundamentals (measures, distributions, variability)
- KPI definitions
- ]Pivot-style summarization
- Trend & comparison views
- Outlier checks
- Simple segmentation
- A guided case study walkthrough from raw data to a management-ready summary
Who Will Benefit:
- Business Analysts
- Data Analysts
- MIS/Reporting Teams
- Finance & Operations Professionals
- Managers who read Dashboards
- Excel/Power BI Beginners who want to Interpret data Correctly