1.6.3: Hands-On Lab Exercise
- Page ID
- 58283
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Lab: Classifying Analytics Types and Mapping the Data Lifecycle
Objective: Apply the analytics type framework and data lifecycle to real-world business scenarios.
Scenario: You are a junior data analyst at FreshGrocer, a regional grocery chain with 50 stores. The VP of Operations has given you a dataset containing 12 months of sales transactions, customer loyalty card data, inventory records, and customer complaint logs. The company wants to understand why certain stores are underperforming.
Instructions:
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Analytics Classification (20 min): The VP has a list of 10 business questions. Classify each as descriptive, diagnostic, predictive, or prescriptive. For each, explain why it fits that category and what data/techniques would be needed.
- "What were total sales by store last quarter?"
- "Why did Store #12 see a 25% sales drop in October?"
- "Which stores are likely to miss their Q1 targets?"
- "What pricing changes should we make to maximize holiday revenue?"
- "How many customer complaints did we receive by category?"
- "What caused the spike in produce waste in November?"
- "Which customer segments are most likely to respond to our new loyalty promotion?"
- "Should we close underperforming stores or invest in renovations?"
- "What is the average basket size by day of week?"
- "What factors distinguish our top-performing stores from bottom performers?"
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Lifecycle Mapping (25 min): Choose one of the predictive or prescriptive questions above and map out how you would address it through all seven stages of the data-to-insight lifecycle. For each stage, specify: what activities occur, what tools/techniques you would use, and what outputs are produced.
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Role Assignment (15 min): For the project you mapped above, describe what tasks a data analyst, data scientist, and data engineer would each handle. Create a RACI matrix (Responsible, Accountable, Consulted, Informed) for at least 5 key tasks.
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Data Source Inventory (15 min): List all internal and external data sources FreshGrocer should collect for their analytics initiative. Categorize each as internal/external and structured/unstructured.
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Executive Summary (15 min): Write a one-page memo to the VP explaining the analytics approach, what types of insights they can expect at each analytics level, and a recommended priority order for tackling the 10 questions.
Deliverables:
- Analytics classification table (10 questions classified with justifications)
- Data lifecycle map for one chosen question
- RACI matrix for team roles
- Data source inventory table
- Executive memo