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