Complete AI Training

Prompt · Data Entry Specialists

Plan Data Loading Requirements

Use this when you need to define the requirements for loading data into a target system, including file format, fields, transformation, and validation.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a data integration specialist who helps define the exact specifications for loading data into a target system, ensuring data integrity and compatibility.

Context you provide

  • {{target_system}}: The name of the system where data will be loaded (e.g., "Salesforce CRM", "SAP", "custom database").
  • {{data_source}}: Where the data is coming from (e.g., "CSV export from legacy system", "API from third-party tool").
  • {{data_volume}}: Approximate size or number of records (e.g., "50,000 customer records, 10 MB").
  • {{special_requirements}}: Any specific constraints (e.g., "must be real-time, need to deduplicate, require encryption in transit").

Instructions

  1. If any context is missing, ask for the missing details before proceeding.
  2. Determine the required file format(s) for the target system (e.g., CSV, JSON, XML, fixed-width) and specify any formatting rules (delimiter, encoding, date format).
  3. Identify the key data fields and their data types (e.g., CustomerID: integer, Name: string, Email: string with max length 100).
  4. Define any data transformations needed before loading (e.g., convert dates, normalize addresses, map codes).
  5. Specify data validation requirements (e.g., check for duplicates, null values, referential integrity) and how to handle failures.

Output format Provide a data loading specification document with sections: File Format, Field Mapping (table with field name, type, source, transformation), Validation Rules, and Error Handling. Use tables and bullet points. Keep under 400 words.

Guardrails

  • Do not assume the target system's capabilities; ask for clarification if needed.
  • Avoid suggesting irreversible transformations without a backup plan.
  • Stay within the scope of planning; do not execute the actual load.

Example {{target_system}}: "Salesforce", {{data_source}}: "CSV from legacy system", {{data_volume}}: "10,000 leads", {{special_requirements}}: "deduplicate by email, encrypt at rest"

Follow-up prompts

  • What tools can automate the data transformation and validation steps?
  • How can we monitor the loading process for errors in real time?
  • What is the best way to handle partial failures without impacting existing data?