Business Intelligence Architectural Stack
Topic: The BI Stack - business intelligence architecture stack. Here is an excellent depiction of the business intelligence architectural stack as envisioned by the analysts at Forrester.
Here at the Dashboard Spy’s Dashboards by Example, we have been focusing on Dashboards (of course!) but are fully aware that they are but a portion of the business intelligence landscape. This excellent diagram shows the place that dashboards have within the entire structure.
Click on the BI Stack Diagram to enlarge the image:
Click on the “more” link to see what Forrester says about the BI Stack.
This from Forrester:
Business Intelligence Is Not Just For Reporting Anymore
Contrary to the common misconception, BI enables more than just reporting and analytics. Forrester defines BI as:
A set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making.
BI requires many different components — sometimes more than 40 — to deliver large enterprise-grade, scalable, robust, secure, and function-rich BI environments (see above figure of the BI Stack). While the Forrester Wave evaluation places heavy emphasis on the reporting, analytics, and information delivery layers of the BI architectural stack, it also addresses dependencies on all the other components like data discovery, integration, and data quality management. Reporting is just the tip of the iceberg.
A decomposition of the BI Stack layer by layer for those of you who want to cut and paste this listing:
Delivery Layer
- Desktop gadgets
- Office suites
- Mobile
- Disconnected
- Portals
- Interactive voice response, ATM, point-of-sale
Reporting Layer
- Dashboards
- Alerts
- Advanced data visualization
- Search
- Geospatial
- Reporting — ad hoc, analytical, production
Performance Management Layer
- Metrics/KPIs
- Planning
- Scorecards
- Strategy/objectives management
Supporting Applications Layer
- Collaboration
- Life-cycle Management
- Localization
- Quality Assurance
- Version Control
- Metadata - integration, repositories
- ECM
- eLearning
- MDM
Analytics
- Data/Text Mining
- Guided Decisions
- NLP
- Guided Search
- Time Series
- OLAP
- Operational DSS
- Predictive Analytics
- Usage analytics
- Statistical analytics
- Web analytics
Discovery and Integration Layer
- Accelerators/query optimization
- Adaptors/toolkits
- BAM/CEP BPM/BRE Integration
- Discovery accelerators
- Data Quality - cleansing, profiling
- EAI/SOA
- EII
- ETL/CDC
- Integration - third party applications
- Operational Data Stores (ODS), Data Warehouses (DW), Data Marts (DM)
- Report Mining
- Services Registry and Repository
Data Layer
- Columnar DBMS
- Hierarchical/XML
- In-Memory DBMS
- Multidimensional OLAP
- Multivalue DBMS
- RDBMS
- Streaming DBMS
- Search DBMS
Infrastructure Layer
- Network
- Servers
- Storage
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Let’s get back to the dashboards!
Small surprise that so much money gets spent with so little visible return.