Big Data

Jargon Watch: Database terms

Database technology allows you to look at customer or sales data upside down and sideways, if you want. This week, we look at key terms that relate to the retrieval and analysis of complex organizational data.


Whether you know a data mart from a warehouse, your career may rise and fall on the quality of the information you use to make business decisions. Whenever you take a look at daily sales figures or forecast long-term revenue, you’re dependent on the information in front of you.
This week’s Jargon Watch puts a handle on online analytical processing (OLAP) terms. Look for next week’s column, where we’ll keep the spotlight on database words.
 

Online analytical processing (OLAP)
OLAP is software technology that allows users to easily and quickly analyze and view data from multiple points-of-view. OLAP provides dynamic and multi-dimensional support to executives and managers who need to understand different aspects of the data.

Activities that are supported include:
  • Analyzing financial trends
  • Creating slices of data
  • Finding new relationships among the data
  • Drilling down into sales statistics
  • Doing calculations through different dimensions where each category of data, (i.e., product, location, sales numbers, time period, etc.) is considered a dimension

Traditional OLAP products are also known as multidimensional OLAP (MOLAP).

Relational OLAP (ROLAP)
ROLAP tools take data from traditional two-dimensional (or relational) databases and create multidimensional views upon request (rather than being prepared in advance, as in OLAP). ROLAP is often used on complex data with a wide number of fields, such as customer data.

Database OLAP (DOLAP)
DOLAP is a relational database management system designed to perform OLAP calculations.

Web OLAP (WOLAP)
WOLAP refers to OLAP data that can be reached from a Web browser.

Data warehouse
As a central storage place for an organization’s data, a data warehouse is larger than an OLAP database. It is set up specifically to support decision-making rather than operations. It provides an enormous amount of historical and static data from three tiers:
  1. Relational databases
  2. Multidimensional OLAP applications
  3. Client analysis tools

A data warehouse facilitates complex data searches, analyses, and queries.

Decision support system (DSS)
A DSS queries a data warehouse or an OLAP database for relevant information that can be compared in order to make a business decision and predict the impact of that decision. For example, it might compare sales figures for two time periods or project revenue figures based on different assumptions.

Data mart
A data mart is an easy-to-access repository of a subset of highly focused data for a single function or department (i.e., finance, sales, marketing) and is considerably smaller than a data warehouse. The data comes from operational information that is needed by a particular group of employees for analysis, content, presentations—all in terms that are familiar to them. Data for a data mart is derived from a data warehouse or from more specialized sources.

Operational data stores (ODS)
If a large database is designed to handle queries on a company’s daily transactions (i.e., sales), it is often known as an operational data store (ODS) rather than a data warehouse.
There is an endless stream of database terms that we could cover. If you would like to submit a term for next week’s Jargon Watch, please send us an e-mail. If you have a comment on this article, please post it below.
 

Mary Ann Fitzharris is a Web editor for TechRepublic. She has thousands of terms stored in her mental data mart.

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