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.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
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
- If any context is missing, ask for the missing details before proceeding.
- 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).
- Identify the key data fields and their data types (e.g., CustomerID: integer, Name: string, Email: string with max length 100).
- Define any data transformations needed before loading (e.g., convert dates, normalize addresses, map codes).
- 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?