EnergyLT Core — Standalone

## The scenario You have joined the Operations Analytics team at a UK domestic energy supplier. The Head of Metering needs a monthly Meter Read Snapshot for the operations review — actual-vs-estimated split, monthly consumption trend, daily-volume outliers, failed reads, and a data completeness dashboard. ## Dataset EnergyLT is a synthetic UK domestic-supply dataset hosted on the CareerSwerve Azure SQL training database. For SQL Core you work exclusively with the `EnergyLT.MeterReading` table — the highest-volume table in the schema and the right place to learn single-table discipline at scale. ## Deliverables Eight outputs (A–H) submitted as a single annotated `.sql` file: **A.** Read type breakdown (Actual / Estimated / Customer / NULL) · **B.** Monthly consumption trend for actual reads only · **C.** Consumption band distribution · **D.** Top 10 highest single-day consumption readings · **E.** Failed read audit (NULL ReadingValue by month) · **F.** Readings in the most recent 30 days · **G.** Actual vs estimated UNION comparison · **H.** Single-row data completeness dashboard. ## Acceptance criteria (summary) Same rigour as PatientLT Core — clean execution, deliberate NULL handling, sargable date filters, logical CASE ordering, report-friendly column aliases, every query commented. The defence emphasises understanding what "estimated read" means commercially and why the actual/estimated split matters for revenue recognition. Full brief and connection details appear inside the lesson once enrolled.