Ad Hoc Query – Ability to create an immediate ‘request for information’ using an analytical reporting tool to answer a specific business-related query.
Aggregation – Predefined summaries based on comprehensive data in the data warehouse.
Atomic data – Topmost level of detail in the data warehouse.
Attribute – Field represented by a column in reports, tables and charts.
Cube – A powerful analysis tool that is used for viewing and analyzing data in a multi-dimensional format, from any angle, in any combination, through a ‘slice and dice’ and drilldown approach.
Data – Factual information for analysis.
Data Mart – A logical subset of related information, typically around one or a few business processes, or a particular subject area.
Data Warehouse – A repository of well-organized corporate data for Business Analysis and Reporting. It is also a collection of data marts.
Database – A collection of data arranged for convenient and quick search and retrieval.
OLAP – Online Analytical Processing is a category of database software that provides an interface to help users quickly and interactively scrutinize the results in a variety of dimensions of the data.
Balanced Scorecard – A Performance management tool that recapitulates an organization’s performance from several standpoints on a single page.
Dashboard – A reporting tool that presents key indicators on a single screen, which includes measurements, metrics, and scorecards.
Data Cube – A multidimensional structure (typically over three dimensions) that forms the basis for analysis applications, allowing various types of calculations and aggregations.
Data Mapping – Process of spotting a source data element for all data elements in the target data warehouse environment.
Data Quality – It is related to facets such as accessibility, comprehensiveness, exactness, steadiness, significance and timeliness of data.
Data staging – A system where operations like data extraction, transformation and loading operations are executed.
Dimension Table – It contains attributes that describe fact records in the fact table. For instance, pupil enrollment is a central fact table with several dimensions linked to it such as Faculty, Term, and Degree.
Drill Down – A feature that allows users to click on an item to navigate through hierarchy and move to a level of better detail.
EIS – Enterprise Information System – A category of applications and technologies for presenting and analyzing corporate and external data for various management purposes.
ETL – Extract, Transform and Load -It is a three-step process at the center of data warehousing. In the first step, operational data is extracted from multiple sources. In the next step, it is transformed into the required type. In the final step, data is loaded into the data warehouse.
Forecasting – It is the formulation of trends, predictive models, and scenarios to prepare for the future for improved decision making.
Gap analysis – Study of whether the available business data supports business requirements, thus answering questions related to data accessibility, amount of data, missing data, and legacy systems. It examines information and decides on the resources and efforts required to satisfy requirements.
Granularity – Level of detail or summarization of data in the data warehouse. The more the detail, the higher the level of granularity.
Institutional performance management – The process of basing an organization’s actions and decisions on actual measured results of performance. It incorporates performance measures, benchmarks, and goals to attain best results.
Measures – A quantifiable, specific piece of information.
Metrics – Measures of performance that observe progress and evaluate trends within an organization.
Normalization – Standard database design technique for relational databases.
Slice and Dice – Multidimensional tools allow users to view data from any angle. The ability to select various angles to view data from is called slice and dice capability.
Snapshot – View of data at a particular moment.