Abstract:
Making effective business decisions with the data is the key to succeeding in today's
competitive environment. Organizations are now looking to improve their decision-making
ability with their current data, but unfortunately operational systems have limited features and
various ad-hoc reports for same data. This unsatisfactory & frustration lead the managers and
IT industry to find new level of applications. These applications focused on ease of analysis
on the single screen to make effective decisions at the time and mining techniques help to
generate new business opportunities by providing prediction oftrends and behaviors as well
as discovery of previously unknown or hidden patterns.
The DSS/B1 systems should have more analyzing features and structured data. But current
OLTP data and its database design not give much more analyzing power. In order to that
OLAP architecture has built from various database vendors to make to use by DSS /BI
systems. The developing of a data warehouse database and Data Mart database with suitable
schema and approaching with relevant architecture is make a foundation for DSS/BI systems
The Data warehouse database makes on available history data as possible of getting last
update record. The fact and dimension structure are used when designing database schema for
Data Warehouse. ETL process generate a data to warehouse from various data sources. The
Data Marts are used for holding various subject areas like sales, purchase, production,
finance, etc. But here only considering about sales and delivery data only. The Data Cube
Technology (OLAP technology) is used for end user to viewing data with various
dimensional and drill-down drill-up processes within the application.
Finally those data are used to mining frequent patterns, Associations and Correlations
between items in menu orders by using apriori algorithm (Microsoft Association algorithm)
and forecasting Predictive sales for each item by using ARIMA algorithm (Mircosoft Time
Series)
The data warehouse solution can be made from by integrating various database technologies
in the middle; those technologies include SQL Server Management Studio (SSMS), SQL
Server Integration Services (SSIS), SQL Server Analysis Server (SSAS), SQL Server Report
Service (SSRS) and SQL Server Data Tools for Visual Studio used to create Analyzing
project and Data mining project. C# language, DMX and MDX queries are used to build the simple mining application.
