Self-Service Analytics AI Prompts

Help me automate a report I currently produce manually so it runs itself and I can focus on analysis instead of assembly. Report I produce manually: {{report_description}} How long it takes me currently: {{time_spent}} Tool I have access to: {{available_tools}} Audience and delivery method: {{audience_and_delivery}} 1. Identify what can be automated vs what requires human judgment: Go through the report and classify each step: - Fully automatable: data pulling, number calculation, chart generation, formatting - Partially automatable: anomaly flagging (automate the detection, human writes the explanation) - Requires human judgment: context, implications, recommendations The goal is to automate the assembly so I can spend my time on interpretation. 2. Automation approach for my tools: If using Excel / Google Sheets: - Data connection: link directly to the data source so the file refreshes automatically - Scheduled refresh: configure the data connection to refresh on a schedule - Email distribution: use a simple script or Zapier to email the report automatically If using Python (low-code approach): - Use pandas to pull and process the data - Use openpyxl or xlsxwriter to generate a formatted Excel report - Schedule with cron (Mac/Linux) or Task Scheduler (Windows) - Send via smtplib or a Slack bot If using a BI tool (Tableau, Power BI, Looker, Metabase): - Set the data source to auto-refresh - Use the built-in subscription feature to email a PDF snapshot on a schedule 3. Build in quality checks: - Before the automated report sends: check that the data was refreshed (compare last update timestamp to expected update time) - Check that key metrics are within a plausible range (alert me if revenue is 0 or 10× normal — likely a data error) - If checks fail: send an alert to me instead of the report to the audience 4. The commentary problem: - Automated reports without commentary are just data dumps - Build a commentary template with fill-in-the-blank sections that I complete in 10 minutes - The template prompts me: 'Key trend this week:', 'Biggest deviation from expectations:', 'Recommended action:' Return: automation approach for my specific tools, quality check implementation, commentary template, and estimated time savings.

Help me create a reusable analysis template so I can repeat this analysis quickly each week or month without starting from scratch. Analysis I do repeatedly: {{analysis_description}} Data source: {{data_source}} Outputs needed: {{outputs}} 1. Template structure: Design a template that: - Has clearly labeled sections I fill in each time (date range, filter criteria, comparison period) - Has fixed sections that stay the same every time (the formulas, the chart types, the table structure) - Is easy to use for someone who did not create it (my colleague should be able to run this without asking me how) 2. What to parameterize (make easy to change): - Date range: make it a single cell reference that all other cells use — change it once, everything updates - Comparison period: prior period, same period last year, target - Filters: which region, product, or segment to include For each parameter: where to put it, how to label it, and what the default value should be 3. What to standardize (keep the same every time): - Column names and order - Chart types and formatting - Metric definitions — write them out once so future-me and colleagues use the same definition - The commentary structure (this forces you to answer the same questions every time, which makes period-over-period comparison easier) 4. Documentation to include in the template: - A brief description of what this template does - Where the data comes from and when it was last refreshed - Definitions of each metric - Known limitations or caveats - Who to contact if something looks wrong 5. The 'can a colleague use this?' test: - Could someone with similar skills use this template without any instructions from you? - What is the most likely point of confusion? Add a note there. Return: a step-by-step template design with all the above elements.

Help me design a simple dashboard that my team can use independently to monitor performance without needing my help. Team: {{team_description}} Key questions they need to answer: {{team_questions}} Tool I will build it in: {{tool}} (e.g. Google Sheets, Excel, Tableau, Power BI, Metabase, Looker Studio) 1. What the dashboard is NOT: - It is not a data dump — every chart and number must answer a specific question - It is not for the builder — design it for people who look at it once a week, not for people who built it - It is not a report — it is a decision-support tool. Every element should prompt an action or confirm that no action is needed. 2. Design the dashboard structure: For each of the team's key questions, specify: - The metric or chart that answers it - The time frame it should show - The comparison context (vs last week, vs target, vs same period last year) - What 'green' looks like (no action needed) and what 'red' looks like (action needed) 3. Layout principles: - Most important metric top left (where eyes go first) - Single number + trend arrow for quick scanning - Detailed breakdowns below for people who want to dig in - Maximum 6–8 metrics on the main view — if you need more, create a second level 4. Making it self-service: - Add filter controls that the team can use to slice by region, product, time period - Color code automatically: green above target, yellow within 10% of target, red below threshold - Add a 'last updated' timestamp so users know if the data is fresh - Include a glossary section that defines every metric 5. Adoption tips: - Walk the team through it once — show them how to answer their 3 most common questions using it - Set a recurring reminder for them to check it at the start of each week - Ask for feedback after 2 weeks: which parts do they use, which do they ignore? Return: dashboard wireframe (described in text), metric definitions, color coding rules, and a 30-minute walkthrough plan for the team.