Data science and data engineering: preparing information for analysis
Preparing data from several systems: business questions, sources, cleaning, shared keys, history, validation and reproducible analysis.
Preparing BI reports: user decisions, metric definitions, data models, refresh, permissions and total validation.
A BI dashboard presents agreed metrics in decision context. Users should understand definitions, periods and sources and be able to investigate deviations. Charts without these rules can look convincing while giving departments incompatible answers.
Define users and decisions such as sales, stock, cost or execution control. Record formulas, events, periods and exceptions. Order revenue and received payments are different figures and should not share ambiguous labels.
For example, a return may arrive in another period. Define its reporting and comparison effects. The owner approves the rule before chart selection.
Link facts and dimensions through validated keys at defined granularity. Incorrect relationships may multiply amounts after joins. Reconcile control results with sources, including filters and grouping.
Define refresh schedules and visible freshness. Source outages should leave users aware of data status. A green chart with stale values must not appear current.
Start with key metrics, deviations and drill-down. Labels, units and scales should aid interpretation. Do not add charts merely to fill space without supporting a user question.
Compare like conditions: calendar, currency, scope and available period. Explain incomplete periods. Colour should not be the sole indicator of important differences.
Define data, report and export permissions. Hidden sheets are not access control. Test each manager’s scope, including direct access and platform capabilities.
A pilot user follows the decision workflow and reconciles figures with agreed examples. Hand over definitions, models, refresh and ownership. Review metrics after business-rule changes so attractive reports remain meaningful.
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Preparing data from several systems: business questions, sources, cleaning, shared keys, history, validation and reproducible analysis.
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