OLAP Architecture at
e-Brainstorm Technology, Inc.
We divide OLAP operational characteristics into three main modules:
OLAP graphical user interface - GUI
OLAP analytical processing logic
OLAP data-processing logic
These three OLAP modules, residing in the client/server environment, make it
possible to use OLAP' s three defining characteristics: multidimensional data
analysis, advanced database support, and easy-to-use end user interface.
ETL - Extraction, Transformation and Load
We utilize ETL to build, deploy, and manage a series of linked, dimensional
data marts to form an integrated business intelligence system. Dimensional data
marts are organized by subject area such as sales, finance and marketing, and
coordinated by data category such as customer, product and location. We deliver
a panoramic view of the key business dimensions for our clients in terms of
time, locations, customers, products, services, accounts and channels.
OLAP - Online Analytical Processing
Multidimensional Data Analysis Techniques
Advanced data presentation functions: 3-D
graphics, pivot tables, cross tabs, data rotation, three-dimensional cubes.
Such data presentation facilities are compatible with desktop spreadsheets,
statistical packages, query and report-writer packages.
Advanced data aggregation, consolidation, and
classification functions: allow the business data analyst to create
multiple data aggregation levels, slice and dice data, drill down and roll up
data across different dimensions and aggregation levels. For example,
aggregating data across the time dimension (by week, month, quarter and year)
allows the business data analyst to drill down and roll up across time
Advanced computational functions:
business-oriented variables (market share, period comparisons, sales margins,
product margins, percentage changes, etc.), financial and accounting ratios
(profitability, overhead, cost allocations, returns, etc.), statistical and
forecasting functions, and so on. These functions are provided automatically,
and the end users do not need to redefine their components each time they are
Advanced data modeling functions: support for
" What-If " scenarios, variable assessment, variable contributions to
outcome, linear programming, and other modeling tools.
Advanced Database Support
Access to many different kinds of DBMSs -
Database Management System, flat files, and internal and external data
Access to aggregated data warehouse data as well as
to the detail data found in operational databases.
Advanced data navigation features such as drill-down
Rapid and consistent query response times.
The ability to map end user requests, expressed in
either business or model terms, to the appropriate data source and then to the
proper data access language (SQL 2000 or Oracle 9i). The query code is
optimized to match the data source, regardless of whether the source is
operational or data warehouse.
Support for very large databases. The data warehouse
can easily and quickly grow to multiple gigabytes and even terabytes
Easy-to-Use End User Interface
The Client/Server architecture provides a framework within which new
systems can be designed, developed, and implemented.
The Client/Server environment enables us to divide an OLAP system into
several components that define its architecture. These components can then be
placed on the same computer or they can be distributed among several
computers. Our OLAP is designed to meet ease-of-use, as well as system
flexibility, and requirements.