ManualsCross Industry46·DA

The Data Analyst
Field Manual

101 prompts for the work a data analyst actually does — data dictionary entry generator, advanced pandas data pipeline script, complex SQL join query.

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Prompt 5 / Data Analyst0/1 filled

Data Dictionary Entry Generator

You are an experienced data analyst responding to this task. I need to create data dictionary documentation for the following database table: . The columns are: [list columns with their data types, e.g., "order_id (INT), customer_id (INT), order_date (TIMESTAMP), total_amount (DECIMAL), status (VARCHAR), discount_code (VARCHAR), shipping_address_id (INT), created_at (TIMESTAMP), updated_at (TIMESTAMP)"]. For each column, generate a data dictionary entry with: (1) **Column name**, (2) **Data type**, (3) **Description** — a plain-English explanation of what this field contains, (4) **Example values** — 2-3 realistic examples, (5) **Nullable** — whether it is likely nullable (Yes/No with reasoning), (6) **Business rules** — any inferred constraints or relationships (e.g., foreign keys, valid ranges, enum values). Format as a markdown table.
Your input: 1 blank. The other 116 words do the thinking for you.

Pages 1, 77 of 101

Two more, straight out of the manual

Prompt 10/2 filled

Advanced Pandas Data Pipeline Script

You are an experienced data analyst responding to this task. Generate a complete Python data pipeline script that does the following: [describe the pipeline, e.g., "Read daily sales data from a CSV, clean and validate it, enrich it with customer data from a PostgreSQL database, calculate derived metrics (7-day moving averages, YoY comparisons), and output a clean analysis-ready parquet file"]. Input: . Output: .
Your input: 2 blanks. The other 64 words do the thinking for you.
Prompt 770/0 filled

Complex SQL Join Query

You are an experienced data analyst responding to this task. I need to write a complex SQL query that joins multiple tables. Here is what I need: [describe the business question, e.g., "For each active customer, show their lifetime revenue, number of orders, most recent order date, their assigned account manager, the account manager's region, and whether the customer has an open support ticket"]. The tables and their relationships are: [describe, e.g., "customers (customer_id, name, status, account_manager_id) → orders (order_id, customer_id, order_date, amount) → support_tickets (ticket_id, customer_id, status, created_date).
Your input: 0 blanks. The other 89 words do the thinking for you.

Contents

Eight chapters, 101 prompts

  1. 01

    Pricing & quoting

    Quotes, hourly rate, value-stack, discount calls

  2. 02

    Estimates & proposals

    On-site walkthroughs, scopes, proposal copy

  3. 03

    Customer communication

    Hard emails, follow-ups, late payment chases

  4. 04

    Scheduling & jobs

    Routing, dispatch, no-show recovery

  5. 05

    Marketing on a budget

    Local SEO, postcards, Google profile, reviews

  6. 06

    Hiring & subs

    Job posts, screening, contractor agreements

  7. 07

    Finances & taxes

    Margin, runway, “should I take this job?” math

  8. 08

    The hard ones

    Firing a client, layoffs, mistakes you made

Can't I just ask ChatGPT to write these myself?

You can — the way you can write your own contracts. Each prompt here encodes what to ask for, what to exclude, and the failure modes to avoid, iterated against real output. $29 skips that work for every job on this page.

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