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MM - Phase 3 - Model Planning

For organizing and enhancing your notes on Phase 3 - Model Planning of the Data Analytics Lifecycle, let's refine the structure and identify keywords or short phrases suitable for creating an effective mind map. This will help in better recall and understanding of the concepts.

Refined Notes on Model Planning

Overview

  • Purpose: Establish methods and workflow for model building.
  • Data Understanding: Analyze relationships and select key variables and models.

Key Activities

  1. Assess Data Structure

    • Tools and Techniques: Evaluate data to choose appropriate tools.
    • Data Assessment: Understanding data formats and quality.

  2. Alignment with Objectives

    • Goal-Oriented Analytics: Ensure techniques align with business goals.
    • Hypothesis Testing: Validate business hypotheses.

  3. Model Complexity

    • Single vs. Multiple Models: Decide on the complexity and integration of models.
    • Workflow Design: Designing analytical workflows.

  4. Research

    • Benchmarking: Study existing solutions to similar problems.
    • Innovation: Incorporate innovative approaches from past projects.

Data Exploration and Variable Selection

  • Visualization: Use tools to visualize data relationships.
  • Stakeholder Input: Incorporate expert opinions and hypotheses.
  • Variable Testing: Iterative refinement to pinpoint key predictors.

Model Selection

  • Technique Alignment: Match techniques with project aims.
  • Model Realism: Models that replicate real-world phenomena.
  • Data Type Consideration: Techniques for different data structures.
  • Tool Implementation: Utilize R, SAS, or Matlab for modeling.

Common Tools

  • R Programming: Versatile for modeling and data analysis.
  • SQL Analysis Services: In-database predictive analytics.
  • SAS/ACCESS: Integration with data sources for seamless analytics.

Simplified Explanation

  • Puzzle Analogy: Planning a puzzle (model) before assembly (building).
  • Strategy and Tools: Choosing strategies and tools based on the puzzle's complexity.

Keywords and Phrases for Mind Map

  • Model Planning: Central node.
  • Data Assessment: Structure, quality.
  • Goal Alignment: Business goals, hypotheses.
  • Complexity Choices: Single model, multiple models, integration.
  • Research and Innovation: Benchmarking, innovative approaches.
  • Exploration: Visualization, stakeholder involvement, refinement.
  • Model Building Tools: R, SAS, Matlab, SQL Services.
  • Real-world Modeling: Techniques, realism, data type.

Using these keywords and phrases in your mind map will help you visually organize the process of model planning, ensuring that each aspect is adequately represented and easy to recall. This structured approach not only aids in memory retention but also in explaining the concepts to others or revisiting them for deeper understanding.