Draft a data transformation logic

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Transformation Steps:

  1. Data Cleansing:
    • Remove Duplicates: Identify and eliminate duplicate transaction records based on transaction ID to ensure data integrity.
    • Handle Missing Values: Fill in or remove records with missing customer or transaction data. For example, if customer demographic information is missing, flag these transactions for further investigation.
    • Standardize Date Formats: Convert the purchase date field into a consistent format (e.g., YYYY-MM-DD) to enable accurate time-based analysis.
  2. Data Enrichment:
    • Join Customer Demographics: Merge the transaction data with a customer demographics table to enhance the dataset with information such as age, gender, and location. This will facilitate demographic-based analysis.
  3. Data Aggregation:
    • Sum Purchase Amount by Category: Group the data by product category and aggregate the total sales amount for each category to prepare for reporting.
    • Calculate Time-Based Metrics: Create derived columns for year, quarter, and month from the purchase date to facilitate time-based performance analysis.
  4. Data Transformation:
    • Normalize Customer Demographics: Create customer segments (e.g., high-value, low-value, new) based on purchase history and demographic characteristics. This will help in targeted analysis by customer profile.
    • Derive New Metrics: Calculate metrics such as average purchase value per customer and total transactions per category to enrich the analysis.
Draft a data transformation logic
23.8827.91
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How to Use Prompts

Step 1: Download the prompt after purchase.

Step 2: Paste the prompt into your text-generation tool (e.g., ChatGPT).

Step 3: Adjust parameters or use it directly to achieve your goals.

Draft a data transformation logic
23.8827.91
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License Terms

Regular License:

  • Allowed for personal or non-commercial projects.
  • Cannot be resold or redistributed.
  • Limited to a single use.

Extended License:

  • Allowed for commercial projects and products.
  • Can be included in resold products, subject to restrictions.
  • Suitable for multiple uses.
Draft a data transformation logic
23.8827.91
Clear