business intelligence process grain of the fact table dr. chang liu
TRANSCRIPT
Business Intelligence Process
Grain of the Fact Table
Dr. Chang Liu
Data
Operational Data Sources (Normalized)
Staging Database
Data Warehouse (Denormalized)
Analysis Services
Multidimensional Cube Data
Client Distributio
n
Business Intelligence Process
* Cubes are normally created as part of a Business Intelligence process.
Data Mart
Data Mart
Business Intelligence Process Demo
Create a dimensional model for a BI application
Use Excel as a front end tool to analyze data
BI Benefits in Modern Organizations
Improvement of Operational Performance
Improvement in Customer Service
Identification of New Opportunities
BI Obstacles/Challenges BI requires large initial investment
BI requires substantial ongoing costs
BI return-on-investment is difficult to justify
Organizations lack of preparation for BI:• Business events are not consistently defined throughout the
enterprise
BI Tools may be difficult to use for certain users
BI for Competitive Advantages? IT and Business together must tackle their
data issues by answering the following questions:
• Data Relevance – what data is needed to complete on analytics?
• Data Sourcing – where can this data be obtained?
• Data Quantity – How much data is needed?• Data Quality – How can the data be made more
accurate and valuable for analysis?• Data Governance – What rules and processes
are needed to manage data from its creation through its retirement?
Reading Assignment
Predicts 2014: Business Intelligence and Analytics will remain CIO’s Top Technology Priority
Analytics 3.0
BI Tools
Personal BI Team BI Organizational BI
PowerPivot for EXCEL(Personal BI)
Example: Sales Data in DB
Sales
Customer_IDSalesman_IDYear_IDMonth_IDDay_IDAmount
Customers
Customer _IDCustomer_Name
SalesMen
Salesman _IDSalesman_Name
Years
Year _IDYear
Months
Month _IDMonth
DayOfWeek
Day _IDDay
The Star Schema
Sales
Customer_IDSalesman_IDPeriod_IDAmount
Customers
Customer _IDCustomer_Name
SalesMen
Salesman _IDSalesman_Name
Periods
Period_IDDate
The Star Schema (2)
What is a Cube? A cube can be thought of as a
multidimensional pivot or crosstab.
It stores numeric values for all combinations of values of the business dimensions.
Grain of the Fact Table
Granularity of Fact Table–what level of detail do you want?
• Finer grains better market basket analysis capability
• Finer grain more dimension tables, more rows in fact table
• In Web-based commerce, finest granularity is a click
Star schema example
Fact table provides statistics for sales broken down by product, period and store dimensions
Size of Fact Table Depends on the number of dimensions and the grain
of the fact table
Number of rows = product of number of possible values for each dimension associated with the fact table
Example: assume the following for Figure 1:
Total rows calculated as follows (assuming only half the products record sales for a given month):
Size of Fact Table (2) The size of the fact table is many times larger than
the dimension tables!
Estimate the size (in bytes) of the fact table:• Each of the above 6 fields average about 4 bytes in length• Total Size = ?
The size of the fact table depends on the number of the dimensions and the grain of the fact table.• Suppose we’d like to request the daily totals be accumulated
in the fact table (assuming 20% of all products record sales on a given day)
• Number of rows in the fact table?• Total Size = ?
Advantages of a Star Schema The star schema is a denormalized schema The star schema has several benefits:
• Simplified the database structure• Easy to query because there is only one level of
joins• Queries run much faster compared to the
normalized structure• Easy to maintain• Modeled around business entities
Class Exercise – Size of a Fact Table
PowerPivotSAP Business Object Explorer
Exercises