Showing posts with label warehouse. Show all posts
Showing posts with label warehouse. Show all posts

Sunday, 27 March 2016

Data Warehouse Glossary #3


Drill Through:
Data analysis that goes from an OLAP cube into the relational database.

Data Warehousing:
The process of designing, building, and maintaining a data warehouse system.

Conformed Dimension:
A dimension that has exactly the same meaning and content when being referred from different fact tables.

Central Warehouse
A database created from operational extracts that adheres to a single, consistent, enterprise data model to ensure consistency of decision-support data across the corporation. A style of computing where all the information systems are located and managed from a single physical location.

Change Data Capture
The process of capturing changes made to a production data source. Change data capture is typically performed by reading the source DBMS log. It consolidates units of work, ensures data is synchronized with the original source, and reduces data volume in a data warehousing environment.

Classic Data Warehouse Development
The process of building an enterprise business model, creating a system data model, defining and designing a data warehouse architecture, constructing the physical database, and lastly populating the warehouses database.

Data Access Tools
An end-user oriented tool that allows users to build SQL queries by pointing and clicking on a list of tables and fields in the data warehouse.

Data Analysis and Presentation Tools

Software that provides a logical view of data in a warehouse. Some create simple aliases for table and column names; others create data that identify the contents and location of data in the warehouse.



Data Dictionary
A database about data and database structures. A catalog of all data elements, containing their names, structures, and information about their usage. A central location for metadata. Normally, data dictionaries are designed to store a limited set of available metadata, concentrating on the information relating to the data elements, databases, files and programs of implemented systems.

Data Warehouse Architecture
An integrated set of products that enable the extraction and transformation of operational data to be loaded into a database for end-user analysis and reporting.

Data Warehouse Architecture Development
A SOFTWARE AG service program that provides an architecture for a data warehouse that is aligned with the needs of the business. This program identifies and designs a warehouse implementation increment and ensures the required infrastructure, skill sets, and other data warehouse foundational aspects are in place for a Data Warehouse Incremental Delivery.

Data Warehouse Engines
Relational databases (RDBMS) and Multi-dimensional databases (MDBMS). Data warehouse engines require strong query capabilities, fast load mechanisms, and large storage requirements.

Data Warehouse Incremental Delivery
A SOFTWARE AG program that delivers one data warehouse increment from design review through implementation.

Data Warehouse Infrastructure
A combination of technologies and the interaction of technologies that support a data warehousing environment.

Data Warehouse Management Tools
Software that extracts and transforms data from operational systems and loads it into the data warehouse.

Data Warehouse Network
An industry organization for know-how exchange. SOFTWARE AG was the first vendor member of the Data Warehouse Network.

Functional Data Warehouse
A warehouse that draws data from nearby operational systems. Each functional warehouse serves a distinct and separate group (such as a division), functional area (such as manufacturing), geographic unit, or product marketing group.

OLTP
On-Line Transaction Processing. OLTP describes the requirements for a system that is used in an operational environment.

Scalability
The ability to scale to support larger or smaller volumes of data and more or less users. The ability to increase or decrease size or capability in cost-effective increments with minimal impact on the unit cost of business and the procurement of additional services.

Schema
The logical and physical definition of data elements, physical characteristics and inter-relationships.

Slice and Dice
A term used to describe a complex data analysis function provided by MDBMS tools.

Warehouse Business Directory
Provides business professionals access to the data warehouse by browsing a catalog of contents.

Warehouse Technical Directory
Defines and manages an information life cycle, a definition of warehouse construction, change management, impact analysis, distribution and operation of a warehouse.

Transformers
Rules applied to change data.



Friday, 18 March 2016

Data Warehouse Glossary #1



Ad Hoc Query:

A database search that is designed to extract specific information from a database.  It is ad hoc if it is designed at the point of execution as opposed to being a “canned” report.  Most ad hoc query software uses the structured query language (SQL).

Aggregation:

The process of summarizing or combining data.

Catalog:

A component of a data dictionary that describes and organizes the various aspects of a database such as its folders, dimensions, measures, prompts, functions, queries and other database objects.  It is used to create queries, reports, analyses and cubes.

Cross Tab:

A type of multi-dimensional report that displays values or measures in cells created by the intersection of two or more dimensions in a table format.

Dashboard:

A data visualization method and workflow management tool that brings together useful information on a series of screens and/or web pages.  Some of the information that may be contained on a dashboard includes reports, web links, calendar, news, tasks, e-mail, etc.  When incorporated into a DSS or EIS key performance indicators may be represented as graphics that are linked to various hyperlinks, graphs, tables and other reports.  The dashboard draws its information from multiple sources applications, office products, databases, Internet, etc.

Cube:

A multi-dimensional matrix of data that has multiple dimensions (independent variables) and measures (dependent variables) that are created by an Online Analytical Processing System (OLAP).  Each dimension may be organized into a hierarchy with multiple levels.  The intersection of two or more dimensional categories is referred to as a cell.


Data-based Knowledge:

Factual information used in the decision making process that is derived from data marts or warehouses using business intelligence tools.  Data warehousing organizes information into a format so that it represents an organizations knowledge with respect to a particular subject area, e.g. finance or clinical outcomes.

Data Cleansing:

The process of cleaning or removing errors, redundancies and inconsistencies in the data that is being imported into a data mart or data warehouse.  It is part of the quality assurance process.

Data Mart:

A database that is similar in structure to a data warehouse, but is typically smaller and is focused on a more limited area.  Multiple, integrated data marts are sometimes referred to as an Integrated Data Warehouse.  Data marts may be used in place of a larger data warehouse or in conjunction with it.  They are typically less expensive to develop and faster to deploy and are therefore becoming more popular with smaller organizations.

Data Migration:

The transfer of data from one platform to another.  This may include conversion from one language, file structure and/or operating environment to another.

Data Mining:

The process of researching data marts and data warehouses to detect specific patterns in the data sets.  Data mining may be performed on databases and multi-dimensional data cubes with ad hoc query tools and OLAP software.  The queries and reports are typically designed to answer specific questions to uncover trends or hidden relationships in the data.

Data Scrubbing:

See Data Cleansing


Data Transformation:

The modification of transaction data extracted from one or more data sources before it is loaded into the data mart or warehouse.  The modifications may include data cleansing, translation of data into a common format so that is can be aggregated and compared, summarizing the data, etc.

Data Warehouse:

An integrated, non-volatile database of historical information that is designed around specific content areas and is used to answer questions regarding an organizations operations and environment.

Database Management System:

The software that is used to create data warehouses and data marts.  For the purposes of data warehousing, they typically include relational database management systems and multi-dimensional database management systems.  Both types of database management systems create the database structures, store and retrieve the data and include various administrative functions.

Decision Support System (DSS):

A set of queries, reports, rule-based analyses, tables and charts that are designed to aid management with their decision-making responsibilities.  These functions are typically “wrapped around” a data mart or data warehouse.  The DSS tends to employ more detailed level data than an EIS.







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