# Glossary | Word | What it means | |---|---| | **Story** | What the data must show, in your words: the numbers, the window and the events ("MRR from $50k to $200k over two years, churn spiking in Q3"). | | **Stated number** | A number in the story that Misata holds exactly: a monthly total, a balance, a rate, a share or an average. | | **Held** | The data shows the stated number, read back in SQL. "Not held" means it could not be, and the dataset says why. | | **Window** | The months the data covers. The last month is the one a dashboard opens on. | | **Event** | A change for a while: a spike, a dip, a campaign, an outage. "5% in Q3 2025" is an event on a 2% rate. | | **Built-in shape** | A business Misata knows in depth (SaaS, e-commerce, banking and payments, health systems and more), with its tables, mechanics and standard metrics. | | **Plan** | What Studio will build, shown before any rows exist: tables, sizes, stated numbers, window and events. | | **Certificate** | The record of what was checked on the finished data: each stated number, each rule, each key, and anything open. Shareable as a public link. | | **Verified** | Every stated number met, every declared rule held, and no critical or major finding open. | | **Realism notes** | Observations about the data (seasons, hours, concentration), with their SQL. They describe; they do not change the verdict. | | **Answer key** | Each metric's SQL and its value in every month of the window, as `answer_key.json` and a CSV. | | **Metric (KPI)** | A number the business reads: MRR, logo churn, billed revenue, win rate, or one you stated. | | **Misreading** | A usual wrong way to compute a metric (churn over every account, not those at risk), measured on the same rows so a wrong answer can be named. | | **Identity** | An equation the data keeps, read in SQL: billed revenue equals MRR; an order's total equals its lines. | | **Checker** | Runs a query, or reads numbers, against the answer key. Names a right one; says what a wrong one computes and how to fix it. | | **Questions** | Plain-language questions drawn from the answer key, each with its answer, its SQL and the wrong answers its misreadings give. | | **Seed** | The number that fixes the random draws. The same request and seed make the same data, byte for byte. | | **Variation** | The same story with a new seed: different rows, the same stated numbers. | | **Revision** | A change to a ready dataset (in words, a story edit, a curve or a control). It makes a new version and checks it; the first is never touched. | | **Curve** | A monthly total you draw; each month lands on it. | | **Control** | A named dial on a dataset (how strongly a cause acts, staff at peak, planted problems), changed on the Adjust tab. | | **Planted problems** | Data-quality issues put in on purpose (duplicates, late records, typos), each listed, for testing cleaning and monitoring. | | **Blueprint** | The engine's own design language: tables, columns, rules, processes and stated numbers, in JSON. What a design becomes before it is built. | | **Backlot demo** | A pipeline (dbt or Postgres) seeded so its own output tells a story, with a room, a reset and an agent endpoint. | | **Demo room** | A Backlot link anyone can open with no account: the story, what the pipeline measured, and a read-only SQL console. | | **Instructions** | Rules every dataset on your account keeps to ("company names fictional"), read as requirements. |