Top 15 Powerful Functionality and Glossary of Standard BI Software
Business intelligence software is getting increasingly more powerful, and although most of the popular solutions on the market share much common functionality, some might be easier to use or offer more or fewer features than others.
Most Used Features are:
- Drill-down and up (on dimensions such as time, company trees, products, etc.)
- Graphs, charting, and trees with custom drill down
- Exception Conditional highlighting cell level
- Pivot Multi Dimensional rows and columns
- Drag and drop dimensions into the current view or to the background and drill it
- Custom calculations (calculate new measures based on existing ones)
- Queries Wizard Expertise
- Comments and Saving of Layout
- Combo views with Cross Tabs
- Dashboards with KPI reports
- Web Portals with RSS feeds
- Distribution of cubes/reports with XML Publishing
- Analytical features (ranking, filtering, sorting, group by etc.)
- Interval Grouping on date field
- Export to PDF, XLS, TXT, HTML etc.
Glossary of few most used BI Terms:
- Ad-Hoc Query: Any query that cannot be determined prior to the moment the query is issued. A query that consists of dynamically constructed SQL, which is usually constructed by desktop-resident query tools.
- Crosstab: A process or function that combines and/or summarizes data from one or more sources into a concise format for analysis or reporting.
- 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. It is catalog of all the data elements, containing their names, structures, and information about their usage which is in 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.
- Datawarehouse: An implementation of an informational database used to store sharable data sourced from an operational database of record. It is typically a subject database that allows users to tap into a company’s vast store of operational data to track and respond to business trends and facilitate BI reporting.
- Decision Support Systems (DSS): Software that supports exception reporting, stop light reporting, standard repository, data analysis, and rule-based analysis. A database created for end-user ad-hoc query processing.
- Dimension: A dimension is a structural attribute of a cube that is a list of members, all of which are of a similar type in the user’s perception of the data. For example, all months, quarters, years, etc., make up a time dimension; likewise all cities, regions, countries, etc., make up a geography dimension. A dimension acts as an index for identifying values within a multi-dimensional array. If one member of the dimension is selected, then the remaining dimensions in which a range of members (or all members) are selected defines a sub-cube. If all but two dimensions have a single member selected, the remaining two dimensions define a spreadsheet (or a “slice” or a “page”). If all dimensions have a single member selected, then a single cell is defined. Dimensions offer a very concise, intuitive way of organizing and selecting data for retrieval, exploration, and analysis.
- Drill Down: A method of exploring detailed data that was used in creating a summary level of data. Drill down levels depend on the granularity of the data in the datawarehouse.
- Enterprise Portal: The enterprise portal offers a web-like solution to the problem of distributing business information, consolidating business intelligence objects (reports, documents, spreadsheets, data cubes, etc.) generated anywhere in the enterprise by any application and making them easily accessible, subject to security authorization, to non technical users via standard browser technology.
- Executive Information Systems (EIS): Tools programmed to provide canned reports or briefing books to top-level executives. They offer strong reporting and drill-down capabilities. Today, these tools allow ad-hoc querying against a multidimensional database, and most offer analytical applications along functional lines such as sales or financial analysis.
- Metadata: Metadata is data about data. Examples of metadata include data element descriptions, data type descriptions, attribute/property descriptions, range/domain descriptions, and process/method descriptions. The repository environment encompasses all corporate metadata resources: database catalogs, data dictionaries, and navigation services. Metadata includes things like the name, length, valid values, and description of a data element. Metadata is stored in a data dictionary and repository. It insulates the datawarehouse from changes in the schema of operational systems.
- Multidimensional Analysis: The objective of multidimensional analysis is for end users to gain insight into the meaning contained in databases. The multidimensional 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 multidimensional 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 multidimensional analysis.
- OLAP: Client End-user applications that can request slices from online analytical processing (OLAP) servers and provide two-dimensional or multidimensional displays, user modifications, selections, ranking, calculations, etc., for visualization and navigation purposes. OLAP clients may be as simple as a spreadsheet program retrieving a slice for further work by a spreadsheet-literate user or as high functioned as a financial modeling or sales analysis application.
- Slice and Dice: A term used to describe a complex data analysis function provided by BI tools.
- Structured Query Language (SQL): A structured query language for accessing relational, ODBC, DRDA, or non relational compliant database systems.
Posted on March 11th, 2008 by Vikram Kole
Filed under: Business Intelligence
Thanks the author!