This document provides an overview of the Business Intelligence portfolio for Joel Chamberlain. It describes the various Microsoft tools used in the BI stack, including Visio for data warehouse design, SQL Server for ETL and querying, SSAS for OLAP cubes and calculations, and reporting tools like Excel, PerformancePoint and SSRS. It includes examples of how each tool is used and configured.

1. Business Intelligence
Portfolio
Joel Chamberlain
joel.chamberlain@setfocus.com

2. The Business Intelligence Stack
 Architecture Design – Visio
 Warehousing – SSMS
 Integration – SSIS
 Analysis – SSAS
 Applications – SSRS, Excel, PPS
 Delivery – MOSS

3. Visio – A Simple Warehouse Design
The following slide demonstrates a source database for
an OLAP cube. The specification calls for a book
publisher to be able to report on book sales by:
1. Customer and customer category
2. Title, title category and price
3. State and region
Author – must have a many to many relationship with
4.
books
5. Calendar date

5. SSMS - Overview
In addition to providing a nice GUI for DBMS
administrative functions, SSMS provides facilities for
developing, organizing and analyzing database queries.

6. SSMS – Job Scheduling
Scheduling routine tasks allows overall system load to
be controlled, so as to minimize impact on users and
system resources.

8. SSMS – MDX Query Design
SSMS provides a convenient platform to development
and manage custom code for use in SSAS, SSRS, and
PPS.

10. SSMS – SQL Query Design
SQL Queries can be tested and tuned.

12. SSMS – Profiler
Server performance can be
monitored, captured and analyzed to aid
troubleshooting and further refine query
execute.

14. SSIS – Overview
SSIS provides the tools to collect records from various
unrelated data sources. The records can be validated
and modified to SQL Server data types. These modified
records are then loaded to a Data Warehouse.

15. SSIS – Extract, Transform, and Load
The following slides demonstrate ETL for a relational
database. The specification calls for consolidating
information from various Excel Workbooks and Flat
Files into a Data Warehouse schema described by this
diagram of the target database.

17. SSIS – Data Flow
SSIS uses packages to organize ETL operations. The
following three slides show the data operations of a
package designed to:
• Search for employee timesheet files
• Convert the data fields to SqlServer data types
• Check the records for valid data
• Upsert them to the appropriate table.
(This package has *not* been optimized for speed).

21. SSIS – Control Flow
The control flow component of this package is depicted
in the next slide. It manages the error logs and emails
the results of the preceding data flow operations. The
‘Get All Timesheets’ Loop Container is where the data
flow is actually executed.

23. SSIS – Package Execution
Packages can be run as steps in a SQL Server Job, or as
tasks in a Sequence Container of a ‘master’ package.
The master package is simply a package that executes
other previously-deployed packages.
The following master package runs all the packages
needed to populate the database, as well as performing
some database maintenance tasks.

25. SSAS – Overview
SSAS is where the data becomes Business Intelligence.
Warehouse data is incorporated in to the OLAP
structures. SSAS Operations include:
• Cube Definition
• Business Calculations
• Key Performance Indicators
• Storage and Security functions

26. SSAS – Cube Design
Cubes are built from Star/Snowflake schemas defined in
the Data Warehouse. Views can be used to select
subsets of the available Warehouse objects for security
or ease of use.

28. SSAS – Business Calculations
In addition to the built-in aggregation functions, custom
measures can be computed using MDX.

30. SSAS – Key Performance Indicators
KPI’s allow for a quick snapshot of the current state of
business processes. Some client applications can
translate these as graphics for quick comprehension on
status dashboards.

32. SSAS – Administration
In addition to Role-based access control to the OLAP
structures, storage options can be tuned to maximize
performance against various operational requirements.

34. – Applications –
Excel, PerformancePoint, SSRS
Excel is BI for the masses, only requiring that Excel 2007
or better is installed on the local machine and an SSAS
database is available. PerformancePoint and SSRS each
provide slightly different features tailored to their
respective environments. As of March
2009, PerformancePoint is scheduled to become part of
Sharepoint Services later this year.

35. Excel Pivot Table and Chart
An interactive pivot table and chart. Users may explore
Enterprise data without waiting for their IS staff to
respond to requests for information.

37. PerformancePoint
An interactive PerformancePoint Dashboard.
PerformancePoint is a server-based environment. This is
an (arguably) more attractive, user friendly, if somewhat
less capable environment for working with Business
Intelligence.

40. SSRS
The SSRS environment is part of SQL Server 2005 or
better. It provides the most comprehensive data and
report formatting, though the user interface may be
somewhat less friendly.

42. Microsoft Office Sharepoint Server
MOSS provides a centralized location for managing the
finished reports. User can interact with, print, save, and
schedule reports for regular delivery in a number of
different formats.