Jeremy BrinkmanDirector of Administrative Systems

University of Northwestern Ohiojbrinkman@unoh.edu

Great Lakes Users’ Group ConferenceAugust 10-11, 2009

Reporting Evolution Why a Data Warehouse? Planning Technologies Used Design Implementation Challenges Resources

Legacy ERP System ◦ (1981-2005)◦ Transactional reporting

Migration to Datatel Colleague / SQL◦ (2005-Current)◦ Transactional reporting◦ Snapshot Reporting

Colleague and the Data Warehouse ◦ (2007-Current)◦ Transactional reporting◦ Snapshot reporting◦ Point-in-time data reporting◦ Ad-hoc reporting

Departments can produce their own reports◦ Empowers end users◦ Reduces the burden on IT

Capture point-in-time data◦ Daily financial standing◦ Daily financial aid award packaging status◦ Active student programs in a term

Reduce performance hit on transactional database server Simplify reporting

◦ SQL version of the Colleague database has 3,000+ tables! Combine disparate data sources

“A lot of times, people don't know what they want until you show it to them.” – Steve Jobs in BusinessWeek, May 25 1998

Meet with the departments with the most ad-hoc data requests◦ Financial Aid◦ Admissions◦ Registration and Advising

Review existing reports for KPIs Involve the decision makers Leverage your tech-savvy users to help drive

adoption

Star vs. Snowflake Schema Fact and Dimension tables Metadata Conformed Dimensions Type One, Two, and Three Slowly Changing

Dimensions Measures Key Performance Indicators (KPIs) Inmon Model vs. Kimball Model

Datatel Colleague Release 18 SQL Server 2005 Business Intelligence Development Studio (BIDS)

◦ To develop the data load processes SQL Server Integration Services (SSIS)

◦ To move data from Colleague to the warehouse◦ Datatel Data Orchestrator ODS

We started before ODS was an option, so we kept SSIS. ODS is a nice tool to get the data from Colleague into SQL, especially for UniData shops

SQL Server Management Studio (SSMS) Business Objects Enterprise XI R2 Web Intelligence (WEBI)

◦ Ad-hoc report development Data Modeling Software

◦ ERWin◦ Power Architect

Uppercase naming in the database Yes/No fields end in _IND Coded fields end in _CODE Description fields end in _DESC Date fields end in _DATE All tables will have a unique key field that identifies the

record. ◦ These fields will include the table name and end in _KEY

Use descriptive names for tables and fields

Star Schema Used Avoid the Snowflake! Central Fact Table Supporting Dimension

Tables Financial Aid Awards by

Term Example

Identify data that will be shared among many subject areas in the warehouse (conformed dimensions)◦ Person Bio/Demo◦ Academic Term◦ Student

Build your dimensions with the assumption that they will be used with other subject areas in the warehouse

Start with a few basic, useful fields per dimension Focus on one department first

◦ Financial Aid was a good starting point for UNOH because they requested the most ad-hoc data and had more tech-savvy users

Focus on one subject area to produce a quick “win”◦ Financial Aid Awards by Term◦ These users will be your evangelists!

SQL Server Integration Services (SSIS) moves the data from the Colleague database to the warehouse

Data is loaded from multiple sources Datatel ODS can also be used as an intermediate data store Load the dimension tables first, then the fact tables

Load a fact table

Load a dimension table

Centralized reporting system Web Intelligence provides ad hoc reporting from the

data warehouse Subject-based data is organized into Universes

◦ Universes store that metadata for the fields in the data warehouse

The Universes add a user-friendly layer to the reporting model

Identify the data subject area Design and build the dimension tables

◦ Data modeling software Design and build the fact table

◦ Data modeling software Build the ETL package and load the tables

◦ Business Intelligence Development Studio◦ SQL Server Integration Services

Build the Business Objects Universe◦ Business Objects Designer

Publish the Universe

WEBI Demo

Getting users to understand the concept of a data warehouse

Learning the technical concepts◦ We are still learning!

Determining where to place the data◦ Fact or dimension table

Finding educational data warehouse examples◦ Business uses a Time dimension , education uses

Term (in most cases)

The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses◦ by Ralph Kimball◦ ISBN: 0-471-15337-0

Other Campus Data Warehouse Sites Google

Jeremy BrinkmanDirector of Administrative SystemsUniversity of Northwestern Ohiojbrinkman@unoh.edu

Great Lakes Users’ Group ConferenceAugust 10-11, 2009