Decision supports Systems Components Data management function Data warehouse Model management function Analytical models: Statistical model, management science model User interface Data visualization

New Developments in Decision Support Systems Data visualization: Representing data in graphical/multimedia formats for analysis. Web-based “dashboards” http://www.corda.com/centerview-executive-dashboard-product-tour.php, Product tour Retail sales Data warehousing What-if scenarios

Data Warehouse A subject-oriented, integrated, time-variant, non-updatable collection of data used in support of management decision-making processes Subject-oriented: e.g. customers, employees, locations, products, time periods, etc. Dimensions for data analysis Integrated: Consistent naming conventions, formats, encoding structures; from multiple data sources Time-variant: Can study trends and changes Nonupdatable: Read-only, periodically refreshed

Data Warehouse Design - Star Schema - Fact table contain detailed business data Ex. Line items of orders to compute total sales by product, by salesperson. Dimension tables contain descriptions about the subjects of the business such as customers, employees, locations, products, time periods, etc.

Periodic extraction  data is not completely current in warehouse The ETL Process L One, company-wide warehouse T E Periodic extraction  data is not completely current in warehouse

The ETL Process Capture/Extract Transform Load and Index Scrub or data cleansing Load and Index ETL = Extract, transform, and load

Example: Order Processing System City OID ODate CID Cname Rating SalesPerson Has M Order Customer 1 M Qty Has M Product Price PID Pname

Star Schema Location CustomerRating Dimension Dimension LocationCode State City CustomerRating Dimension Rating Description FactTable LocationCode PeriodCode Rating PID Qty Amount Can group by State, City Period Dimension PeriodCode Year Quarter Product Category CategoryID Description Product Dimension PID Pname CategoryID

From SalesDB to MyDataWarehouse Extract data from SalesDB: Create query to get the data Download to MyDataWareHouse File/Import/Save as Table Transform: Transform City to Location Transform Odate to Period Query FactPC Load data to FactTable

On-Line Analytical Processing (OLAP) Tools The use of a set of graphical tools that provides users with multidimensional views of their data and allows them to analyze the data using simple windowing techniques Relational OLAP (ROLAP) Traditional relational representation Multidimensional OLAP (MOLAP) Cube structure OLAP Operations Cube slicing–come up with 2-D view of data Drill-down–going from summary to more detailed views Roll-up – the opposite direction of drill-down Reaggregation – rearrange the order of dimensions

Slicing a data cube

Example of drill-down Summary report Starting with summary data, users can obtain details for particular cells Drill-down with color added

Geological Information System GIS GIS is a computer-based tool for mapping and analyzing things that exist and events that happen on earth. GIS technology integrates common database operations such as query and statistical analysis with the unique visualization and geographic analysis benefits offered by maps.

Data of GIS Geodatabase: Attribute data: Example: Google Earth A geodatabase is a database that is in some way referenced to locations on the earth. Longitude, latitude Attribute data: Attribute data generally defined as additional information, which can then be tied to spatial data. Example: Google Earth

Scenario A scenario is an assumption about input variables. Excel’s Scenarios is a what-if-analysis tool. A scenario is a set of values that Microsoft Excel saves and can substitute automatically in your worksheet. You can use scenarios to forecast the outcome of a worksheet model. You can create and save different groups of values on a worksheet and then switch to any of these new scenarios to view different results.

Creating a Scenario Tools/Scenarios Demo: benefit.xls Add scenario Changing cells Resulting cells Demo: benefit.xls

Chart

Charting Decision Rules An Internet Service Provider charges customers based on hours used: First 10 hours $15 Each of the next 20 hours $2 per hour Hours over 30 hours $1 per hour

Comparing Decision Rules Plan 2: First 20 hours: $20 Hours over 20 $1.5 Plan 3: $35 unlimited access.

Charting Functions Demand function: P = 150 – 6*Q^2 Supply function: P = 10* Q^2 + 2*Q Note: Positive area Value axis maximum/minimum value: Format Value Axis