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If you do not see a particular word or phrase that you would like to know the definition of, please let us know by writing to MaryJo.Nott@sourcemedia.com and indicate the term you would like us to add to the Glossary.
- Magic Arrow
- An arrow used in marketing materials that gives the illusion of an integrated and automated process.
- Managed Availability
- The ability of an organization to deliver consistent, predictable access to information for any user wherever, whenever and however the user needs it.
- Market Basket
- The term "market basket" refers to a specific type of basket or a fixed list of items used specifically to track the progress of inflation in an economy or specific market. The list used for such an analysis would contain a number of the most commonly bought food and household items. The variations in the prices of the items on the list from month to month give an indication of the overall development of price trends.
- Market Segmentation
- Segmentation is the process of partitioning markets into
groups of potential customers with similar needs and/or
characteristics who are likely to exhibit similar purchase
- Market Share
- A companys sales expressed as a percentage of the sales
for the total industry.
- Marketing Resource Management
- Marketing resource management (MRM) refers to software that helps with the upfront planning of a marketing function and the coordination and collaboration of marketing resources.
- Mass customization
- The use of technology, such as the internet, to deliver
customized services on a mass basis. This results in giving
each customer whatever they ask for.
- Master Data
- Master data represents the parties to the transactions that record the operations of an enterprise. Two examples are customer and product.
- Master Data Management
- Master data management (MDM) is business context data that contains details (definitions and identifiers) of internal and external objects involved in business transactions (e.g., customer, product, reporting unit, NPS, market share). It explains the context within which you do business and holds the business rules.
Master data management is a series of processes put in place to ensure that reference data is kept up to date and coordinated across an enterprise.
Master data management is the organization, management and distribution of corporately adjudicated information with widespread use in the organization.
- Meta Data
- Meta data is data that expresses the context or relativity of data. Examples of meta data include data element descriptions, data type descriptions,
attribute/property descriptions, range/domain descriptions
and process/method descriptions. The repository
environment encompasses all corporate meta data resources:
database catalogs, data dictionaries and navigation
services. Meta data includes name, length, valid values
and description of a data element. Meta data is stored in
a data dictionary and repository. It insulates the data
warehouse from changes in the schema of operational
- Meta Data Synchronization
- The process of consolidating, relating and synchronizing
data elements with the same or similar meaning from
different systems. Meta data synchronization joins these
differing elements in the data warehouse to allow for
- Meta Muck
- An environment created when meta data exists in multiple
products and repositories (DBMS catalogs, DBMS
dictionaries, CASE tools warehouse databases, end-user
tools and repositories).
- A system of principles, practices, and procedures applied to a specific branch of knowledge.
- A framework to establish and collect measurements of
success/failure on a regulated, timed basis that can be
audited and verified.
- Microsimulation is a computational technique used to predict the behavior of a system by predicting the behavior of microlevel units that make up the system.
- Mid-Tier Data Warehouses
- To be scalable, any particular implementation of the data access environment may incorporate several intermediate distribution tiers in the data warehouse network. These intermediate tiers act as source data warehouses for geographically isolated sharable data that is needed across several business functions.
- A communications layer that allows applications to interact across hardware and network environments.
- Mini Marts
- A small subset of a data warehouse used by a small number of users. A mini mart is a very focused slice of a larger data warehouse.
- A query that consumes a high percentage of CPU cycles.
- An acronym for millions of instructions per second. MIPS is
mistakenly considered a relative measure of computing
capability among models and vendors. It is a meaningful
measure only among versions of the same processors
configured with identical peripherals and software.
- To represent how a business works and functions in such a way that it can productively be used as a means to simulate the real world. Executives, planners, managers and analysts use modeling to simulate and test operational and financial planning assumptions.*
- Massive Parallel Processing. The "shared nothing" approach of parallel computing.
- Multi-Value Attribute
- Multi-value is a database model with a physical layout that allows systematic manipulation and presentation of messy, natural, relational, data in any form, first normal to fifth normal.
- Data structure with three or more independent dimensions.
- Multidimensional Array
- A group of data cells arranged by the dimensions of the
data. For example, a spreadsheet exemplifies a two-
dimensional array with the data cells arranged in rows and
columns, each being a dimension. A three-dimensional array
can be visualized as a cube with each dimension forming a
side of the cube, including any slice parallel with that
side. Higher dimensional arrays have no physical metaphor,
but they organize the data in the way users think of their
enterprise. Typical enterprise dimensions are time,
measures, products, geographical regions, sales channels,
- Multidimensional Database (MDBS and MDBMS)
- A powerful database that lets users analyze large amounts
of data. An MDBS captures and presents data as arrays that
can be arranged in multiple dimensions.
- Multidimensional Query Language
- A computer language that allows one to specify which data
to retrieve out of a cube. The user process for this type
of query is usually called slicing and dicing. The result
of a multi-dimensional query is either a cell, a two-
dimensional slice, or a multi-dimensional sub-cube.
- Multidimenstional Analysis
- The objective of multi-dimensional analysis is for end
users to gain insight into the meaning contained in
databases. The multi-dimensional approach to analysis
aligns the data content with the analyst's mental model,
hence reducing confusion and lowering the incidence of
erroneous interpretations. It also eases navigating the
database, screening for a particular subset of data, asking
for the data in a particular orientation and defining
analytical calculations. Furthermore, because the data is
physically stored in a multi- dimensional structure, the
speed of these operations is many times faster and more
consistent than is possible in other database structures.
This combination of simplicity and speed is one of the key
benefits of multi-dimensional analysis.
* definition provided by Hyperion.