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

2. New Developments in Decision Support Systems
Data visualization: Representing data in graphical/multimedia formats for analysis.
Web-based “dashboards”
Product tour
Retail sales
Data warehousing
What-if scenarios

3. 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

4. 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.

5. 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

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

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

8. 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

9. 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

10. 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

11. Slicing a data cube

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

13. 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.

14. 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

15. 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.

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

17. Chart

18. 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

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

20. 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