I mainly write this post for novices who need to begin with Business Intelligence and to be aware of the most Business Intelligence keywords thus they could read any Business Intelligence article without any problem.
Business Intelligence: The art of extracting right information in timely manner to right person from raw data, it doesn’t depend on specific technology but very wide of technologies depend on; like Data Mining. It makes the organization realize its resources, potential and give the Big Image* to the status of its goals.
Operational Business Intelligence: Business Intelligence Systems build on the same Business Intelligence process ETL, Analysis then Reporting but they don’t care about KPIs and Measures more than data listing.
Tactical Business Intelligence: Business Intelligence Systems build on the same Business Intelligence process ETL, Analysis then Reporting beside they give a wide solutions to tactical managers who can use them to get the most of KPIs (Profit in dollars, number of CRM tickets, etc) to take their organization step towards its goals.
Strategic Business Intelligence: Business Intelligence Systems build on the same Business Intelligence process ETL, Analysis then Reporting it helps the top management get the status -very brief status- of the organizations and its step towards its goals.
Measure\Fact: What’s the organization looks for, profit in currency, revenue, number of user come to website, number of CRM tickets, etc…
Dimension: How the Measure\Fact measured per, means profit in currency (Measure\Fact) can be measured per time, sales region, sales person, product type, etc.. so we call time, sales region, sales person, product type dimensions. Simply everything you can group by…
Hierarchy dimension: Dimension has self-relationship like time dimension we may see Year, Quarter, Month, Week, Day and may be more deep details. Simply everything with more than one level (deparment employee).
Attribute: Fact\Dimension property like Currency dimension may have currency name in English, currency name in Arabic; those are attributes.
Calculated member: Is a more comlicated calculation derived from the existing measures.
Data Mart: Dimension and Facts for specific department in the organization.
Data Warehouse: Big datamarts connected together.
ROLAP: Relational-OLAP: OLAP architecture where data stored in relational database where there’s no limit for data storage.
MOLAP: multidimensional-OLAP: OLAP architecture where data stored in multidimensional cube for fast retrieval for data and for executing very complicated queries.
HOLAP: Hybird-OLAP: OLAP architecture combines the both of ROLAP and MOLAP
Snowflake Schema: Data mart schema where Measures connected to Facts, but hierarchies dimensions not in one table like Time dimension, we have Year dimension connection with Month which connects with Day and so on.
Star Schema: Data mart schema where Measures connected to Facts, and all hierarchies dimensions exist in one table, in Time dimension example we find Year, Month, Day, etc. data exists on one table.
Report: form to list all data in tubular or matrix format where use can drill through to find more information about something.
KPI: Key Performance Indicator, $200 million is success to organization X? for sure the answer is I don’t know. so KPI come to say if the profit is more than H we made success and if it lower than L then we didn’t manage to achieve our target. so in scorecards we use some symbols like green light in case the measure exceeds the KPI. so dashboards depend on the KPI to give the right view to top management users because they just understand numbers.
Dashboard: Interactive report with various charts which state the status of organization POI, users can drill through and drill down to see more and more details.
Scorecard: Very interactive report with a lot of symbols and less words, for strategic managers depends mainly on KPIs.
ETL: refers to Extract, Transform and Load process which happens in the most Business Intelligence solutions to get data from different heterogenous sources, cleansing it then load it to the data warehouse.
OLAP: OnLine Analytical Processing, the stage to analyze the data to get the information.
OLTP: Online Transactional Processing simply is the backend data repository for any business application; It maintains data for business process and it’s from the sources of ETL process.
Data Mining\Forecasting: Built-in algorithms use to predicate the future based on existing data.
Cube: Microsoft term which represents “Data Mart”.
*I quoted it from my manager Yasmeen El-Nizamy (Senior BI Developer | LINKDev)
Do you see, you can make it better, please send me at ramymahrous[at]gmail[dot]com