When teaching people about business intelligence (BI), data integration and data warehousing, after introductions and reviewing the syllabus or agenda, I present my jargon and acronym slide. I always tease that there will be a quiz on these terms. I do this with people from IT, business groups, software vendors or students (in a Master’s degree program at an engineering university.) It does not matter what the technical expertise of the crowd –…
When teaching people about business intelligence (BI), data integration and data warehousing, after introductions and reviewing the syllabus or agenda, I present my jargon and acronym slide. I always tease that there will be a quiz on these terms. I do this with people from IT, business groups, software vendors or students (in a Master’s degree program at an engineering university.) It does not matter what the technical expertise of the crowd – they always laugh.
Any IT specialty has its jargon, but we seem to have more than our share in business intelligence. Having a lot of terms and acronyms is usually fine, but in BI we do not always agree on the definition and, even worse, we sometimes use different terms for the same thing.
If the experts, industry analysts and pundits cannot agree then how does everyone else understand what is going on? How do people learn this field and leverage others’ experiences?
My New Year’s wish is that it becomes easier for people to get through the jargon and build or have access to better BI solutions.
My jargon list includes these terms or acronyms:
- Business Intelligence (BI)
- Performance Management (PM)
- Operational BI
- On-Line Analytical Processing (OLAP)
- MOLAP, ROLAP, DOLAP
- Analytical Applications
- Predictive Analytics
- “Slice & Dice” and Drill down
- Data Mining
- Data Visualization
- Dashboards, Scorecards
- Key Performance Indicators (KPIs)
- Data Shadow Systems or Spreadmarts
- DW & BI Appliances
- Data Warehouses (DW)
- Enterprise Data Warehouse (EDW)
- Data Marts (DM)
- Operational Data Stores (ODS)
- Hub & Spoke Architecture
- Data Integration
- Extract, Transform & Load (ETL)
- Enterprise Application Integration (EAI)
- Enterprise Information Integration (EII)
- Extract, Load & Transform (ELT)
- Change Data Capture (CDC)
- SOA (Service Oriented Architecture)
- Real-time Access, BI, DI or DW
- SaaS (Software-as-a-Service) or On-Demand Software versus On-Premise Software
- Cloud Computing
- E/R Modeling versus Dimensional Modeling
- Dimensions & Facts
- Star & Snowflake Schemas versus 3NF (3rd Normal Form)
- Conformed Dimensions
- Slowly Changing Dimensions (SCD)
- MDM (Master Data Management)
- CDI (Customer Data Integration)
- PIM Product Information Management)
- Open Source Software (OSS)
- Relational versus Columnar Databases
- Unstructured Data
- Enterprise Data Mashups
- Data Governance
- Metadata Management
- Enterprise Information Management (EIM)
- BICC (BI Centers of Excellence)
- ICC (Integration Centers of Excellence)
- Data quality (DQ) & data cleansing
- SMP versus MPP
Happy New Year
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