
Question : How do I improve the performance of my Data Mart ?
Every DBMS produces what is called an Execution Plan for every SELECT statement.
The steps to improving the
performance involve checking this Execution Plan against the Indexes that
exist, and making sure that the Query Optimizer has used the appropriate
Indexes to obtain the best performance.
This is a specialized area
where DBA’s spend a lot of their time when they are
looking after production databases where speed is a mission-critical factor.
Data Marts are always created
to support Business Intelligence, which includes Performance Reports, Balanced
Scorecards, Dashboards, Key Performance Indicators and
so on.
Best practice always requires
user involvement and a generic design to support a flexible approach to meeting
changing requirements.
Users will always want
changes to their first specifications of their requirements.
The insight that they obtain
from the first Reports helps them identify more precisely
what their long-term requirements will be.
Therefore flexibility is important.
A well-designed Data Mart will
anticipate the areas where flexibility is required.
The design process should
always follow two steps :-
A range of Data Mart diagrams
is available in the Case Study Chapters.
This example is a Data Model
for a Generic Data Mart for Customers.
The Customer Types include
Parking Ticket Holders and Voters

If you have a requirement
that is not included here, please contact us by email at barryw@databaseanswers.org and we
will help you to get started.
Data Modeling Tools are used
to create Data Marts and here is a sample of the most popular Tools available :-
This Tutorial defines a step-by-step Approach to the design of a Generic Data Mart.
Performance tuning is
important after the Data Mart is up and running.
Microsoft’s Unified Data
Model (UDM) is a Generic approach.
Here is a series of Steps in
designing a Database :-
Step 1. Establish the User Requirements
Step 2. Identify the Data Sources
Step 3. Define the Data Mart and ensure that that the design
supports the User Requirements.
Step 4. Obtain Sample data
Step 5. Produce first draft Reports and review with the
Users.
Step 6. Confirm Data Mart design.
Step 7. Verify end-to-end data flows..
The first step is to think
about the Data Mart as a place where you simply throw all available data and
provide ‘hooks’ so that any combination of data can easily be retrieved.
Briefly, the Key fields in
Tables involved become Dimensions in a Data Mart.
Facts include all the basic
data plus any derived data, typically averages, percentages and totals under
various headings.
To be successful in designing
Data Marts it is important to have a talent for visualizing the User’s
Requirements and for translating this to a formal design of Dimensions and Facts,
together with the most important aspect, which is the derivation of the data
required from the underlying basic data.