A Data Warehouser’s Vocabulary (Part 2)
This post is part 2 (read part 1) of a series of posts containing a glossary of terms and concepts that I feel has some relevance to the data warehousing and business intelligence world. Each of these definitions has a citation; I am using the XHTML “cite” tag with each. If you would like to see the source, view the source! When finished, these terms will be compiled and made a static page on TmF.
- Aggregation
- The process of redefining data into a summarization based on some rules or criteria. Aggregation may also encompass de-normalization for data access and retrieval.
- Analytical Processing
- Producing analysis for management decisions, usually involving trend analysis, drill-down analysis, demographic analysis, profiling, and so on.
- Attribute
- Any detail that serves to qualify, identify, classify, quantify, or express the state of an entity.
- Data Mining
- The process of analyzing large amounts of data in search of previously undiscovered business patterns.
- Dimension
- A denormalized table in a dimensional model with a single part primary key and descriptive attribute columns.
- Event
- A signal that some activity (usually a business transaction) has occurred.
- Fact
- Central table of a Star Schema which numeric performance measurements identified by a composite key, each of whose elements is a foreign key drawn from a dimension table.
- Heuristic Analysis
- Heuristic Analysis is a method to help to solve a problem, commonly informal. It is particularly used for a method that often rapidly leads to a solution that is usually reasonably close to the best possible answer. Heuristics are “rules of thumb”, educated guesses, intuitive judgments or simply common sense.
- Online Analytical Processing (OLAP, also MOLAP)
- On-line retrieval and analysis of data to reveal business trends and statistics not directly visible in the data directly retrieved from a data warehouse. Also known as multidimensional analysis.
- Outrigger
- A secondary dimension table attached to a dimension table. An outrigger is not used to normalize a dimension.
- Relational OLAP (ROLAP)
- “Relational” OLAP, in which the OLAP processes use a relational, normalized model for its source.
- Slowly Changing Dimension (SCD)
- The tendency for dimension attributes to change gradually or occasionally over time. The techniques for handling these changes include Type 1 (overwrite), Type 2 (keep history), and Type 3 (alternate realities).
- Snowflake
- A normalized dimension where a flat, single dimension table is deconstructed into a tree structure with potentially many nesting levels. Snowflaking a dimension generally compromises user understandability and browsing performance.
- Snowflaking
- The (undesirable) act of normalizing a dimensional model.
- Star Schema
- A generic representation of a dimensional model in a relational database in which a fact table with a composite key is joined to a number of single level dimension tables, each with a single primary key.
Data Warehousing and Business Intelligence consultant, with expertise in business analysis, data modeling, and data integration. Extensive experience developing vertical and integrated desktop and Internet applications spanning municipal, clinical, and financial industries.
June 13th, 2008 at 7:47 am
[…] A Datawarehouser’s Vocabulary (Part 2) When finished, these terms will be compiled and made a static page on TmF. Aggregation: The process of redefining data into a summarization based on some rules or criteria. Aggregation may also encompass de-normalization for data access … […]