What is OLAP?

OLAP (Online Analytical Processing) is a category of software technology that enables analysts to interactively examine multidimensional data from multiple perspectives — slicing, dicing, drilling down, rolling up, and pivoting — to support fast, complex analytical queries over large historical datasets (as opposed to OLTP, which handles fast simple transactions).

Main Components of a Data Warehouse System

 ┌────────────┐    ┌───────────────┐    ┌────────────────┐    ┌──────────┐
 │  Source    │───▶│  Extraction/  │───▶│   Data          │───▶│  OLAP /  │
 │  Systems   │    │  Transform/   │    │   Warehouse     │    │  Query   │
 │            │    │  Load (ETL)   │    │   Storage       │    │  Tools   │
 └────────────┘    └───────────────┘    └────────────────┘    └──────────┘
                            │                     │
                            ▼                     ▼
                    ┌───────────────┐    ┌────────────────┐
                    │   Metadata     │    │   Data Marts    │
                    │   Repository   │    │  (subject-wise) │
                    └───────────────┘    └────────────────┘

1. Source/Operational Systems — OLTP databases, external feeds, legacy files that supply raw data.
2. Extraction, Transformation, Loading (ETL) tools — pull data out of sources, clean/standardize it, and load it into the warehouse.
3. Metadata Repository — stores "data about data": schema definitions, source mappings, transformation rules, and refresh schedules.
4. Data Warehouse (central repository) — the integrated, subject-oriented store, typically organized as fact and dimension tables.
5. Data Marts — smaller, department/subject-specific subsets of the warehouse (e.g., Sales mart, HR mart) for faster, focused access.
6. OLAP Servers — ROLAP (relational), MOLAP (multidimensional), or HOLAP (hybrid) engines that serve multidimensional queries.
7. Front-End Analysis/Reporting Tools — dashboards, query tools, data mining tools used by business analysts and decision-makers to consume the data.

Together, these components move data from scattered operational systems into a single, query-optimized structure, and then expose it through OLAP for fast, flexible analysis.