Business Intelligence Cheat Sheet

Updated 2026-04-27

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Business Intelligence is the strategic framework that transforms raw data into actionable insights through analytics, reporting, and visualization. At its core, BI bridges the gap between data collection and business decision-making by enabling organizations to discover patterns, measure performance, and predict outcomes. The most critical distinction in modern BI is the shift from reactive reporting to proactive, AI-augmented analytics where insights are delivered automatically rather than requiring manual exploration—this fundamental change is reshaping how organizations compete on data.

What This Cheat Sheet Covers

This topic spans 16 focused tables and 152 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core BI ConceptsTable 2: Data Modeling ApproachesTable 3: ETL and Data IntegrationTable 4: Query Languages and ExpressionsTable 5: OLAP OperationsTable 6: Key Performance IndicatorsTable 7: Chart Types and Visual SelectionTable 8: Visualization and ReportingTable 9: Data Quality and GovernanceTable 10: Analytics Types and TechniquesTable 11: BI Architecture PatternsTable 12: Performance OptimizationTable 13: Advanced BI CapabilitiesTable 14: BI Tools and PlatformsTable 15: Data Integration and DeliveryTable 16: Emerging Trends and Best Practices

Table 1: Core BI Concepts

Concept	Example	Description
Data Warehouse	`SELECT * FROM sales_fact` `WHERE year = 2026`	• Centralized repository storing structured, historical data optimized for querying and reporting • uses ETL to integrate data from multiple sources.
OLAP (Online Analytical Processing)	`SELECT SUM(revenue)` `FROM sales_cube` `GROUP BY product, region, time`	Multidimensional analysis technology enabling fast aggregation, drill-down, and slice-and-dice operations on large datasets.
Data Lakehouse	`CREATE TABLE bronze.raw_logs` `USING DELTA` `LOCATION 's3://lake/'`	• Unified architecture combining data lake flexibility with data warehouse performance • supports structured and unstructured data with ACID transactions.
Self-Service BI	Drag-and-drop dashboard builder with no SQL required	User-driven analytics enabling business users to create reports and dashboards without IT or data team intervention.
Data Mart	`CREATE VIEW finance_mart AS` `SELECT * FROM warehouse` `WHERE dept = 'Finance'`	• Department-specific subset of a data warehouse • provides focused, fast access to relevant data for a single business unit or team.

Table 1: Core BI Concepts

Concept	Example	Description
Data Warehouse	`SELECT * FROM sales_fact` `WHERE year = 2026`	• Centralized repository storing structured, historical data optimized for querying and reporting • uses ETL to integrate data from multiple sources.
OLAP (Online Analytical Processing)	`SELECT SUM(revenue)` `FROM sales_cube` `GROUP BY product, region, time`	Multidimensional analysis technology enabling fast aggregation, drill-down, and slice-and-dice operations on large datasets.
Data Lakehouse	`CREATE TABLE bronze.raw_logs` `USING DELTA` `LOCATION 's3://lake/'`	• Unified architecture combining data lake flexibility with data warehouse performance • supports structured and unstructured data with ACID transactions.
Self-Service BI	Drag-and-drop dashboard builder with no SQL required	User-driven analytics enabling business users to create reports and dashboards without IT or data team intervention.
Data Mart	`CREATE VIEW finance_mart AS` `SELECT * FROM warehouse` `WHERE dept = 'Finance'`	• Department-specific subset of a data warehouse • provides focused, fast access to relevant data for a single business unit or team.