Business intelligence (BI) has long been a vital tool for forecasting and
budgeting. Since organizations often generate budgets at a high level of detail
before gathering input at lower levels, BI applications are in a unique
position to service the high-level budgeting process. BI databases store the
comprehensive, aggregate data from prior years that anchors the creation of new
budgets. BI also supports the process of improving budgeting quality over time
by comparing prior budgets to their actual execution.
BI is an excellent source of forecasts. Sales managers, business analysts, and
other executives employ various forecasting techniques to predict the
performance of the business over the coming periods. With BI, forecasting
methods can be compared to prior year results in BI applications to identify
which prove most effective over time. BI’s reporting capabilities can be
leveraged to disseminate budgeting and forecasting data around an organization.
Data mining technology leverages the wealth of knowledge stored in BI databases
to make these and other applications of BI data possible. Data mining
techniques provide insight into how a business really operates, and how it can
be made to operate better. By applying one or more algorithms to the data
stored in business intelligence solutions, business can use data pattern
discovery to increases cross-selling performance, data exploration to identify
seasonal trends in sales, time series analysis to generate forecasts over
variable timelines, and other methods to generate a wealth of insight into
business operations.
Microsoft has embedded cutting-edge data mining technology in SQL Server 2005,
making it freely available to businesses that have BI solutions on the
platform. Northridge Systems has the expertise to implement data mining,
forecasting, and budgeting for its clients with SQL Server 2005. With data
mining technology prevailing across a variety of industries in the last few
years, there has never been a better time to see how data mining can open new
pathways to enhanced performance for your business.
Technology Overview
In 2000, Microsoft created what were meant to be several industry standards for
data mining. Years later, the OLE DB for Data Mining specification and Data
Mining Extensions (DMX) query language have become standard interfaces to data
mining objects and algorithms on various data mining platforms.
With SQL Server 2000, Microsoft embedded data mining technology in its business
intelligence platform. Now a generation advanced, the SQL Server 2005 platform
uses the OLE DB and DMX standards to provide data mining capability. SQL Server
Analysis Services 2005 includes 7 algorithms for data mining: Microsoft
Association Rules, Microsoft Clustering, Microsoft Decision Trees, Microsoft
Linear Regression, Microsoft Logistic Regression, Microsoft Naïve Bayes,
Microsoft Neural Network, Microsoft Sequence Clustering, and Microsoft Time
Series. These algorithms can be applied to warehouse data stored SQL Server and
other SQL platforms, or in multidimensional (OLAP) data stored in Analysis
Services 2005.
Since it can be queried directly with an open query language, the output from
SQL Server data mining can be used in a variety ways. Data mining info can be
shown directly in reports, can be used to drive actions in other applications
(such as suggesting cross-selling items in websites and Point-of-Sale systems),
and can generate advanced data visualizations through interfaces in business
analytical tools, SQL Server’s Business Intelligence Development Studio, and
other graphical data interfaces.
Northridge Systems implements the data mining capabilities of SQL Server 2005 to
provide robust, flexible, and cost effective data mining applications that can
provide unique competitive advantages to its clients.
For more detailed information about Business Intelligence services offered by
Northridge Systems, please send us an
information request or email sales@northridge.com
