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MM - Phase 2 - Data Preparation

Structured Notes on Phase 2: Data Preparation

Phase 2: Data Preparation

Overview: Data preparation is the process of assembling, organizing, and cleaning data for analysis. This phase transitions from business understanding to handling data specifics, akin to prepping ingredients for cooking to ensure they're ready for use.

Key Processes:

  1. Preparing the Analytic Sandbox:

    • Creation of Sandbox: Establish a dedicated analytic space for safe data manipulation.
    • Data Collection: Aggregate diverse data types for comprehensive analytics.

  2. Performing ETLT (Extract, Transform, Load, Transform):

    • Extraction and Loading: Retrieve data from sources and load it into the sandbox.
    • Transformation: Apply business rules to modify and structure data for analysis.

  3. Learning About the Data:

    • Data Acquisition: Gather data via external sources, internal entry, or sensor outputs.
    • Data Understanding: Assess the origins and characteristics of the data.

  4. Data Conditioning:

    • Cleaning and Normalizing: Enhance data quality and uniformity through meticulous preprocessing.
    • Data Transformation: Adjust data to fit analytical needs, handled by data specialists.

  5. Involvement of Data Scientists:

    • Collaborative Preparation: Engage data scientists early in the process for optimal preparation.
    • Quality Assurance: Leverage their expertise to refine data for advanced analytical processes.

  6. Common Tools for Data Preparation:

    • Hadoop: Facilitates large-scale data processing.
    • Alpine Miner: Streamlines creation of analytic workflows.
    • OpenRefine: Specializes in refining messy data.
    • Data Wrangler: Assists in data cleansing and transformation.

Analogy: Preparing data is similar to setting up for baking a cake—establish a clean workspace (sandbox), gather and prepare ingredients (data sources and ETLT), understand each component’s role (learning about the data), and ensure all ingredients are prepped correctly for the recipe (data conditioning) with the right kitchen tools (data preparation tools).

Keywords for Mind Map Creation

  1. Analytic Sandbox

    • Create, Safe Environment, Data Aggregation

  2. ETLT Process

    • Extract, Transform, Load, Structured Data

  3. Learning About Data

    • Acquire, Understand Sources, Data Nature

  4. Data Conditioning

    • Clean, Normalize, Transform, Data Quality

  5. Data Scientist Involvement

    • Engage Early, Maximize Data Potential

  6. Tools for Data Preparation

    • Hadoop, Alpine Miner, OpenRefine, Data Wrangler

These structured notes and keywords provide a clear roadmap for creating an effective mind map, ensuring that the essential elements of Data Preparation are easily accessible and memorable.