Specify metrics
Document the unit, denominator, owner and reporting window.
Business and customer analytics · EDITION 1.0.0
Design Dashboards Around Real Decisions
Design a compact operational dashboard around documented decisions, denominator and freshness guards, and an inspectable rule-evaluation tool.
By Sanjaay Gowda T S · For business analysts, dashboard designers and operational service owners.
You need: Basic spreadsheet arithmetic and familiarity with the topic; Python 3.10+ and a terminal for the optional companion project
Runtime and hardware details
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Basic spreadsheet arithmetic and familiarity with the topic; Python 3.10+ and a terminal for the optional companion project.
Full setup and scope ↓$2.99USD · one-time purchase
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review remains pending. Automated checks and agent review are not certification.
PDF + EPUB + companion project. Any applicable tax is shown at checkout. Single-reader ebook terms; companion code is MIT licensed.
TRY THE FREE SAMPLE
See how the guide teaches.
Read 7 sample pages to explore the introduction, first chapter and teaching approach before you choose the complete edition.
Read free sample PDF · No checkout required
WHAT YOU WILL LEARN
Understand each part.
Inspect every boundary.
Guard decisions
Withhold actions when data is stale or insufficient.
Test usefulness
Use scenarios to check whether a dashboard changes a decision.
INSIDE THE BOOK
9 focused chapters.
- Start with the decision and owner
- Write a metric contract
- Choose denominators and comparison windows
- Define thresholds without pretending certainty
- Design views that explain the next action
- Handle freshness and missing evidence
- Run the decision rule evaluator
- Test a dashboard with realistic scenarios
- Maintain definitions and retire unused views
Your download includes
- 23-page tagged PDF with linked contents
- Reflowable EPUB for ebook readers
- Local Python project, fictional input, recorded expected JSON output and 18 companion tests
- 3 explanatory diagrams
- 9 chapters with exercises and worked answers
Before you begin
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Learning prerequisites: Basic spreadsheet arithmetic and familiarity with the topic; Python 3.10+ and a terminal for the optional companion project.
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review is pending.
The included examples are synthetic teaching material. Model access, software subscriptions, hosting, ongoing updates and consulting are not included.
CLEAR EXPECTATIONS
Before you buy.
What will I build?
Design a compact operational dashboard around documented decisions, denominator and freshness guards, and an inspectable rule-evaluation tool. The local companion uses fictional teaching fixtures. Project limits: Supplied thresholds are operational policy, not statistical anomaly detection. Ratios can exceed one for count-per-opportunity metrics. The tool checks values and freshness, not source accuracy or chart accessibility.
What was tested?
The 18 companion tests passed on the packaged project. The supplied fictional fixture produced its recorded expected JSON output. EPUBCheck reported no errors or warnings; DAISY Ace and PDF/UA automated checks passed. These local teaching checks are not production accuracy claims or certification. Independent human technical, editorial and assistive-technology reader review remains pending.
How do I get the files?
Complete the secure Lemon Squeezy checkout to access the PDF, EPUB and companion ZIP. Keep your receipt and download access private. This is a one-time purchase of edition 1.0.0; ongoing updates and consulting are not included.
Can I share the book or the companion code?
The full ebook is licensed to one reader. The labelled free sample may be shared unchanged. The companion project is MIT licensed and may be adapted or shared with its licence notice. See the exact ebook terms.
Attach metrics to owners, thresholds, freshness and useful next actions
One book. A complete learning project. Evidence you can inspect.
AI-assisted · Independent human review pending
$2.99USDBuy ebook