Business Intelligence & Dashboards
Executive reporting, visual hierarchy, dashboard UX, and enterprise metric tracking.
Transforming raw data into actionable business insights, dashboards, metrics, and KPI models.
Subtopics Library
Executive reporting, visual hierarchy, dashboard UX, and enterprise metric tracking.
Relational database query design, star schema modeling, aggregation logic, and data lakes.
Topic Feed · Data Analytics
Combine Power BI Performance Analyzer with DAX Studio Server Timings and Query Plan to locate and fix slow DAX measures.
Use a Field Parameter with a SWITCH‑based master measure to dynamically swap DAX calculations in Power BI reports.
Use a bridge table with inactive relationships and activate them via USERELATIONSHIP or TREATAS to safely handle many‑to‑many in Power BI.
Window functions compute rankings, offsets, and cumulative metrics in one pass, cutting I/O and eliminating self‑joins.
Data Vault 2.0 captures raw events in Hubs/Links/Satellites for auditability, while Kimball builds star schemas for fast analytics; choose based on audit needs vs query speed.
Combine covering/filtered indexes, proper MAXDOP, and targeted hints after profiling to achieve sub‑second queries on multi‑million‑row tables.
Type 1 overwrites rows, Type 2 inserts versioned rows, and Type 3 keeps a single prior value in extra columns.
Compose reusable dbt models, tests, and macros for modular, testable pipelines, then run incrementally with schema validation.
Data lakes store raw data cheaply and provide versioned, schema‑on‑read access, while warehouses deliver fast, curated analytics on curated models.
Interpreting PostgreSQL `EXPLAIN (ANALYZE, BUFFERS)` involves analyzing actual runtime statistics, buffer usage, and planner estimates to pinpoint query bottlenecks and I/O inefficiencies.
Choose B-Tree for general equality/range, GIN for full-text/array/JSONB containment, GiST for spatial/range types and k-NN, and BRIN for large, naturally ordered tables.
Optimize PostgreSQL autovacuum by tuning `autovacuum_vacuum_scale_factor`, `autovacuum_vacuum_threshold`, `autovacuum_freeze_max_age`, and `autovacuum_max_workers` globally and with table-specific overrides to prevent transaction ID wraparound and table bloat.
Leverage PostgreSQL 16's declarative `RANGE` partitioning on time-series data to accelerate historical queries by enabling efficient partition pruning, reducing I/O, and streamlining data management.
Eliminate N+1 query bottlenecks in Laravel by using Eloquent's `with()` method for eager loading, which fetches all associated data in a minimal number of optimized queries, significantly reducing database load and improving application performance.
PgBouncer provides essential connection pooling for PostgreSQL, proxying connections to efficiently manage and reuse them, significantly reducing overhead and boosting scalability for high-concurrency web applications.