Business Analytics for Decision Making
COM1MN110 - Business Analytics for Decision Making study notes and resources. Browse module-wise notes, preview available PDF resources, and use the related links on this page to move between nearby subjects and study guides.
Chapter Wise Notes
About This Subject
Business Analytics for Decision Making (Course Code: COM1MN110) is an analytical minor course for B.Com Semester 1 under Calicut University FYUGP 2026. Designed for the data economy, this course introduces commerce students to how corporate decision-makers transform raw operational data into predictive insights. Students examine the three tiers of business analytics (Descriptive, Predictive, Prescriptive), the data lifecycle, data visualization techniques, business intelligence tools, executive dashboard design, exploratory data analysis (EDA), and data-driven decision-making (DDDM) frameworks.
Key Topics Covered
- Introduction to business analytics: evolution, definitions, and importance in competitive advantage
- The analytics spectrum: descriptive analytics, predictive analytics, and prescriptive analytics
- The business data lifecycle: data acquisition, cleaning, preprocessing, transformation, and storage
- Exploratory Data Analysis (EDA): summary statistics, outlier detection, and data pattern recognition
- Data visualization principles: choosing the right chart (bar, line, scatter, heatmaps, boxplots)
- Business Intelligence (BI) concepts, architectures, and automated dashboard reporting
- Data-driven decision making (DDDM) frameworks: identifying metrics, KPIs, and hypothesis testing
- Ethical considerations in business analytics: data privacy, algorithmic governance, and security
Learning Outcomes
- Understand the role of business analytics across corporate finance, marketing, and operations.
- Classify business analytical problems into descriptive, predictive, or prescriptive paradigms.
- Perform exploratory data analysis and identify data anomalies, trends, and patterns.
- Design intuitive business dashboards and select appropriate data visualizations for executive communication.
- Apply data-driven decision-making frameworks to solve real-world commercial dilemmas.
Exam Preparation Tips
In Part B, explain the 3 tiers of analytics (Descriptive, Predictive, Prescriptive) with a concrete corporate example (e.g., e-commerce, banking). For essay questions, prepare the business data lifecycle from data ingestion to decision execution, and discuss the role of KPIs in modern business intelligence dashboards.
Frequently Asked Questions
What is Business Analytics for Decision Making about?
It covers data analytics tiers, exploratory data analysis, data visualization, business intelligence dashboards, and data-driven decision frameworks.
Which semester includes COM1MN110?
It is an analytical minor in B.Com Semester 1 under Calicut University FYUGP 2026.
Where can I find notes for Business Analytics for Decision Making?
Module lecture summaries and PDF study materials are available on DegreeLive.
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