Glossary: Glossary

Glossary

aggregation: a summary of detail data that is stored with or referred to by a cube. Aggregations support rapid and efficient answers to business questions.
aggregation table: a table that contains pre-calculated totals. Aggregation tables can be referred to by cubes, reducing the amount of time that is required for building the cubes.
Application Response Measurement: the name of an application programming interface that was developed by an industry partnership and which is used to monitor the availability and performance of software applications. ARM monitors the application tasks that are important to a particular business. Short form: ARM.
ARM: See Application Response Measurement.
base table: a table that contains detail data that is used for building cubes or aggregation tables.
calculated member: in a dimension, a member whose value is derived from the values of other members.
child: within a dimension hierarchy, a descendant in level n-1 of a member that is at level n. For example, if a Geography dimension includes the levels Country and City, then Bangkok would be a child of Thailand, and Hamburg would be a child of Germany.
connection profile: a client-side definition of where a metadata server is located. The definition includes a computer name and a port number. In addition, the connection profile can also contain user connection information.
cube: a logical set of data that is organized and structured in a hierarchical, multidimensional arrangement. A cube is a directory structure, not a single file. A cube includes measures, and it can have numerous dimensions and levels of data.
data cleansing: the process of eliminating inaccuracies, irregularities, and discrepancies from data.
data scrubbing: another term for data cleansing. See also data cleansing.
data sparsity: a characteristic of a multidimensional data source in which there is a relatively high proportion of empty cells (which indicate missing data values) to filled cells.
data warehouse: a collection of data that is extracted from one or more sources for the purpose of querying and analysis.
descendant: in a dimension hierarchy, a member that resides at a lower level in relation to other members in the hierarchy. For example, if a Geography dimension includes the levels Country, State, and City, then California and Los Angeles would be descendants of USA.
detail data: nonsummarized (or partially summarized) factual information that pertains to a single area of interest, such as sales figures, inventory data, or human-resource data.
dimension: a group of closely related hierarchies. Hierarchies within a dimension typically represent different groupings of information that pertains to a single concept. For example, a Time dimension might consist of two hierarchies: (1) Year, Month, Date, and (2) Year, Week, Day. See also hierarchy.
dimension table: in a star schema, a table that contains the data for one of the dimensions. The dimension table is connected to the star schema's fact table by a primary key. The dimension table contains fields for each level of each hierarchy that is included in the dimension.
drill down: in a view of an OLAP cube, to start at one level of a dimension hierarchy and to click through one or more lower levels until you reach the data that you are interested in.
drill up: in a view of an OLAP cube, to start at one level of a dimension hierarchy and to click through one or more higher levels until you reach the level of summarized data that you are interested in.
drill-through table: a view, data set, or other data file that contains data that is used to define a cube. Drill-through tables can be used by client applications to provide a view from processed data into the underlying data source.
fact: a single piece of factual information in a data table. For example, a fact can be an employee name, a customer's phone number, or a sales amount. It can also be a derived value such as the percentage by which total revenues increased or decreased from one year to the next.
fact table: the central table in a star schema. The fact table contains the individual facts that are being stored in the database as well as the keys that connect each fact to the appropriate value in each dimension.
foreign key: a column or combination of columns in one table that references the corresponding primary key in another table. A foreign key must have the same attributes as the primary key that it references.
granularity: the relative level of detail that a data item represents. From the top of a dimension to the bottom, granularity increases. For example, in a Time dimension that consists of a Year-Month-Day hierarchy, Month is more granular than Year, and Day is more granular than Month.
hierarchy: an arrangement of members of a dimension into levels that are based on parent-child relationships. Members of a hierarchy are arranged from more general to more specific. For example, in a Time dimension, a hierarchy might consist of the members Year, Quarter, Month, and Day. In a Geography dimension, a hierarchy might consist of the members Country, State or Province, and City. More than one hierarchy can be defined for a dimension. Each hierarchy provides a navigational path that enables users to drill down to increasing levels of detail. See also member and level.
HOLAP: See hybrid online analytical processing.
hybrid online analytical processing: a type of OLAP in which relational OLAP (ROLAP) and multidimensional OLAP (MOLAP) are combined. In HOLAP, the source data is usually stored using a ROLAP strategy, and aggregations are stored using a MOLAP strategy. This combination usually results in the smallest amount of storage space. In HOLAP, aggregates can be pre-calculated and can be linked into a hybrid storage model. Short form: HOLAP.
informat: a pattern or set of instructions that SAS uses to determine how data values in an input file should be interpreted. SAS provides a set of standard informats and also enables you to define your own informats.
leaf member: the lowest-level member of a hierarchy. Leaf members do not have any child members.
level: an element of a dimension hierarchy. Levels describe the dimension from the highest (most summarized) level to the lowest (most detailed) level. For example, possible levels for a Geography dimension are Country, Region, State or Province, and City.
logical server: in the SAS Metadata Server, the second-level object in the metadata for SAS servers. A logical server specifies one or more of a particular type of server component, such as one or more SAS Workspace Servers.
MDDB: See multidimensional database.
MDX language: See multidimensional expressions language.
measure: a special dimension that contains summarized numeric data values that are analyzed. Total Sales and Average Revenue are examples of measures. For example, you might drill down within the Clothing hierarchy of the Product dimension to see the value of the Total Sales measure for the Shirts member.
member: a name that represents a particular data element within a dimension. For example, September 1996 might be a member of the Time dimension. A member can be either unique or non-unique. For example, 1997 and 1998 represent unique members in the Year level of a Time dimension. January represents non-unique members in the Month level, because there can be more than one January in the Time dimension if the Time dimension contains data for more than one year.
metadata server: a server that provides metadata management services to one or more client applications. A SAS Metadata Server is an example.
MOLAP: See multidimensional online analytical processing.
multidimensional database: another term for cube. Short form: MDDB. See also cube.
multidimensional expressions language: a standardized, high-level language that is used to query multidimensional data sources. The MDX language is the multidimensional equivalent of SQL (Structured Query Language). Short form: MDX language.
multidimensional online analytical processing: a type of OLAP that stores aggregates in multidimensional database structures. Short form: MOLAP.
multi-threading: See threading.
navigate: to purposefully move from one view of the data in a table (or in some other data structure, such as a cube) to another. Drilling down and drilling up are two examples of navigation.
NWAY aggregation: the aggregation that has the minimum set of dimension levels that is required for answering any business question. The NWAY aggregation is the aggregation that has the finest granularity. See also granularity.
ODBO: See OLE DB for OLAP.
OLAP: See online analytical processing.
OLAP schema: a group of cubes. A cube is assigned to an OLAP schema when it is created, and an OLAP schema is assigned to a SAS OLAP Server when the server is defined in the metadata. A SAS OLAP Server can access only the cubes that are in its assigned OLAP schema.
OLE DB for OLAP: an OLAP API that is used to link OLAP clients and servers by means of a multidimensional expressions (MDX) language. Short form: ODBO. See also multidimensional expressions language.
online analytical processing: a software technology that enables users to dynamically analyze data that is stored in multidimensional database (MDDB) tables. Short form: OLAP.
parallel I/O: a method of input and output that takes advantage of multiple CPUs and multiple controllers, with multiple disks per controller to read or write data in independent threads.
parallel processing: a method of processing that divides a large job into several smaller jobs that can be executed in parallel on multiple CPUs.
parent: within a dimension hierarchy, the ancestor in level n of a member in level n-1. For example, if a Geography dimension includes the levels Country and City, then Thailand would be the parent of Bangkok, and Germany would be the parent of Hamburg. The parent value is usually a consolidation of all of its children's values.
primary key: a column or combination of columns that uniquely identifies a row in a table.
reach-through: the act of retrieving and displaying to a user the (unsummarized) detail data from which the summarized data in a multidimensional database is derived, when that detail data is stored in a separate data repository.
relational online analytical processing: a type of OLAP in which the multidimensional data is stored in a relational database. Short form: ROLAP.
ROLAP: See relational online analytical processing.
roll up: to summarize (or apply some other type of calculation or formula to) data values at one level of a dimension hierarchy in order to derive values for a parent level. For example, sales figures for January can be rolled up to Quarter1, and employee data for one department can be rolled up to the division level.
SAS application server: a server that provides SAS services to a client. In the SAS Open Metadata Architecture, the metadata for a SAS application server specifies one or more server components that provide SAS services to a client.
SAS ARM interface: an interface that can be used to monitor the performance of SAS applications. In the SAS ARM interface, the ARM API is implemented as an ARM agent. In addition, SAS supplies ARM macros, which generate calls to the ARM API function calls, and ARM system options, which enable you to manage the ARM environment and to log internal SAS processing transactions. See also ARM (Application Response Measurement).
SAS format: a pattern or set of instructions that SAS uses to determine how the values of a variable (or column) should be written or displayed. SAS provides a set of standard formats and also enables you to define your own formats.
SAS informat: a pattern or set of instructions that SAS uses to determine how data values in an input file should be interpreted. SAS provides a set of standard informats and also enables you to define your own informats.
SAS Management Console: a Java application that provides a single user interface for performing SAS administrative tasks.
SAS Metadata Server: a multi-user server that enables users to read metadata from or write metadata to one or more SAS Metadata Repositories. The SAS Metadata Server uses the Integrated Object Model (IOM), which is provided with SAS Integration Technologies, to communicate with clients and with other servers.
SAS OLAP Cube Studio: a Java interface for defining and building OLAP cubes in SAS System 9 or later. Its main feature is the Cube Designer wizard, which guides you through the process of registering and creating cubes.
SAS OLAP Server: a SAS server that provides access to multidimensional data. The data is queried using the multidimensional expressions (MDX) language.
SAS Open Metadata Architecture: a general-purpose metadata management facility that provides metadata services to SAS applications. The SAS Open Metadata Architecture enables applications to exchange metadata, which makes it easier for these applications to work together.
Scalable Performance Data Engine: a SAS engine that is able to deliver data to applications rapidly because it organizes the data into a streamlined file format. The SPD Engine divides a problem (such as a WHERE clause) into smaller problems that can be processed in parallel. Short form: SPD Engine. See also parallel processing.
schema: a map or model of the overall data structure of a database. An OLAP schema specifies which group of cubes an OLAP server can access.
scrubbing: another term for data cleansing. See also data cleansing.
slice: a subset of data from a cube, where the data in the slice pertains to one or more members of one or more dimensions. For example, from a cube that contains data about customer feedback, one slice might pertain to feedback on one particular product (one member of the Product dimension). Another slice might pertain to feedback on that product from customers residing in particular geographic areas who submitted their feedback during a certain time period (one member of the Product dimension, multiple members of the Geography dimension, one or more members of the Time dimension).
SMP: See symmetric multiprocessing.
sparsity: See data sparsity.
SPD Engine: See Scalable Performance Data Engine.
SQL: See Structured Query Language.
star schema: tables in a database in which a single fact table is connected to multiple dimension tables. This is visually represented in a star pattern. SAS OLAP cubes can be created from a star schema.
stored statistics: statistics that are stored in a cube. Stored statistics can be used to derive higher-level statistics. Examples include sum, minimum, and maximum.
Structured Query Language: a standardized, high-level query language that is used in relational database management systems to create and manipulate database management system objects. Short form: SQL.
symmetric multiprocessing: a hardware and software architecture that can improve the speed of I/O and processing. An SMP machine has multiple CPUs and a thread-enabled operating system. An SMP machine is usually configured with multiple controllers and with multiple disk drives per controller. Short form: SMP.
thread: a single path of execution of a process in a single CPU, or a basic unit of program execution in a thread-enabled operating system. In an SMP environment, which uses multiple CPUs, multiple threads can be spawned and processed simultaneously. Regardless of whether there is one CPU or many, each thread is an independent flow of control that is scheduled by the operating system. See also symmetric multiprocessing, thread-enabled operating system, and threading.
thread-enabled operating system: an operating system that can coordinate symmetric access by multiple CPUs to a shared main memory space. This coordinated access enables threads from the same process to share data very efficiently.
threading: a high-performance method of data I/O or data processing in which the I/O or processing is divided into multiple threads that are executed in parallel. In the boss-worker model of threading, the same code for the I/O or calculation process is executed simultaneously in separate threads on multiple CPUs. In the pipeline model, a process is divided into steps, which are then executed simultaneously in separate threads on multiple CPUs. See also parallel I/O, parallel processing, and SMP (symmetric multiprocessing).
Time dimension: a dimension that divides time into levels such as Year, Quarter, Month, and Day.
tuple: a data object that contains two or more components. In OLAP, a tuple is a slice of data from a cube. It is a selection of members (or cells) across dimensions in a cube. It can also be viewed as a cross-section of member data in a cube. For example, ([time].[all time].[2003], [geography].[all geography].[u.s.a.], [measures].[actualsum]) is a tuple that contains data from the Time, Geography, and Measures dimensions.
wizard: an interactive utility program that consists of a series of dialog boxes, windows, or pages. Users supply information in each dialog box, window, or page, and the wizard uses that information to perform a task.

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