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Business Intelligence Initiative AIRPO Conference June 18, 2008 Presented by : Helen Ernst What is a Data Warehouse?

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business intelligence initiative

Business Intelligence Initiative

AIRPO Conference

June 18, 2008

Presented by : Helen Ernst

what is a data warehouse
What is a Data Warehouse?

The data warehouse is a collection of data that is pulled together primarily from operational business systems and is structured and tunedfor easy accessand useby information consumersand analysts, especially for the purpose of decision making.

what is business intelligence software
What is ‘Business Intelligence’ software?

A set of concepts and methods to improve business decision making by using fact-based support systems. BI is sometimes used interchangeably with briefing books, report and query tools and executive information systems. Business Intelligence systems are data-driven DSS(decision support services).

the fundamental goal
The Fundamental Goal

The fundamental goal of the SUNY Data Warehouse Initiative is to integrate administrative data into a accurate,consistent, and reliable information resource that supports planning, forecasting, and decision-making processes at SUNY.





Mission, Goals, Strategy ->Defining measurable outcomes (KPI)


Budgets, Plans, Forecasts, Models -> Set Targets




Alerts -> Actions, Decisions, Adjust plans


Dashboards Business Intelligence


transactional vs analytical systems
Organized and managed to support transaction processing

Organized data based on specific business operations (registration, alumni, giving)

Efficient, inserts and updates

Standards and consistency within each operational area

Data is constantly changing

Stable systems

Requires high level of computing skills.

Organized and managed based on reporting & analytical needs

Integrating and Organizing data into subject areas across business operations

Efficient, fast retrieval

Enforces standards and consistency in data across functional areas

Preserves historical and current information

Adaptive systems

Appeals to wide range of computing skills

Transactional vs.. Analytical Systems


Analytical and Reporting

establishing analytical culture
Executive sponsorship

Requires marketing and communication to all levels of the institute

Organizational will and accountability – DW Group

Close collaboration between IT and the functional units

Establishing Analytical Culture


dw results data quality
DW Results: Data Quality

Common definitions Consistency

Reinforces Institution’s rules and definitions Integrity

Processes, technology, and people revealing data entry errors Accuracy

Central repository  ensures “One Version of the Truth” Reliability


results effectiveness
Results: Effectiveness

Empowers decision-makers by enabling direct access to accurate, consistent, and non-volatile information – this is the heart of business intelligence.

Redirects costly personnel hours from data gathering, matching, and consolidating to data analysis while reducing the need for information workers to replicate data and maintain redundant tracking (shadow) systems.

suny proof of concepts
SUNY Proof of Concepts
  • UB: Strategic Information Reporting Initiative (SIRI)
    • Contact: Joe Kerr
  • OSA: University Business Intelligence Data Management
    • Contact: Helen Ernst
  • OSA: Banner Reporting and Analytics
    • Contact: Ron
suny obiee projects

Buffalo University

Project Lead – Joe Kerr

Strategic Information Reporting Initiative (SIRI)

Develop a complete strategy and implementation plan for aggregating and integrating the various sources of information that are important to the strategic, managerial, and operational concerns of the university and its units and departments. Create an easy and straightforward interface that can be used by unit CFO’s, department managers, and central administrators to access, interpret, and report the data.

suny obiee projects14

System Administration

Project Lead – Helen Ernst

Consultants on site starting 1/27 for 6 weeks

Proof of Concept

The goal of the University Business Intelligence Data Management project is to leverage the existing SUNY Data Warehouse located at System Administration to present data and comprehensive management reporting directly to the desktops of Executive and Senior and middle management.

suny obiee projects15

System Administration

Project Lead – Ron Brown

Implement OBIEE using Banner using Fredonia data stored in ODS (Operational Data Store) at Oneonta, OBI server in Buffalo

Implement OBIEE Plus using a server at ITEC (located at Buffalo State College) and Banner test data stored in ODS (Operational Data Store) at SICAS (located at Oneonta)

poc goals
POC Goals

Single Point Of Entry (web or portal)

Single Source Of Truth

Single Sign-On: Shibboleth / Federated Identity Model

Security: Table, Column, Row

Multiple Locations - Can access / interconnect multiple OBIEE Plus servers and other IT resources at different locations

Integration of dashboards

poc goals17
POC Goals

Assess the end user experience using OBIEE Plus vs. traditional reporting like SQR.

Demonstrate ease of use regardless of skill level; executive, faculty, student, alumni, community ,etc.

Determine if OBIEE Plus can be used for reporting and analytics from other sources, such as: Foundations, Auxiliary Services, Book Store Systems, Parking Systems, other data campus needs BI information.

poc goals18
POC Goals

Determine viability of the level of reporting and analytics that can be reasonably done by users. I.e., Ad hoc reporting and analytics.

Determine viability to create custom reports and dashboards with minimal IT support.

Integrate with SUNY preferred applications.

Provide campus access to public data

Provide public access to appropriate data.

security requirements
Security Requirements
  • Integrate with Single Sign-on
  • Use Initialization Blocks (Queries)
  • Session Variables & Header Records
  • Longer Term Vision, Shibboleth Identity & Federated Model
lessons learned21
Lessons Learned

Senior Management Commitment, translated into organization commitment is critical - Without Management you get nothing

Build a good project team, including a Steering committee and a working group - Without people you get nothing

Provide leadership for the initiative and its projects

Thank people for the great job they are doing - include end users

lessons learned22
Lessons Learned

Collaboration and communication cannot be an afterthought and don’t loose site of it for the initiative and each of its projects.

Making the sale never stops

Focus on management, customers, team, vendor, data owners, etc.

Formal milestones tied to estimate and timeframe reviews / updates

Will your Data Authorization process survive ODS / DW / BI?

lessons learned23
Lessons Learned
  • Data is the most critical piece of the solution, once that is in place and done well the rest is considerably easier, though not without challenge.
  • Having the “data” correct and accessible then allows the “information” to be meaningful.
  • Balance data quality solutions at the source vs. in the ETL vs. time.
    • Real solutions happen at the source
  • Did you count on having to address the data issues you find during the ETL process? And, fast?
lessons learned24
Lessons Learned

You will need more time for testing than you put in your plan.

Ask yourself periodically, how am I making my customer’s lives better? Am I?

Address issues and problems as soon as they appear

Deploy Business Intelligence tools and solutions in a systematic and consistent manner.

lessons learned25
Lessons Learned

Partner with consultants, make them part of the team

Consultants need ownership and risk as well.

Make sure each project has an end. The initiative will go on.

Plan who will support what you build

lessons learned26
Lessons Learned

Provide a stream of deliverables, and gradually scale up the audience.

It will take longer and more resources than you think.

Weekly status updates, open communication channels, and trust.

You need to be able to openly discuss problems and challenges.

Technology is not the hard part….

lessons learned27
Lessons Learned

This is NOT an IT Project, it is Everyone’s Project! Management to end users and vendors.

Weekly status updates and open communications lead to trust. It must be earned.

You need to be able to openly discuss problems and challenges.

Technology is not the hard part….

lessons learned28
Lessons Learned

The key to standardizing Business Intelligence tools is to make them conform to the way your users work / think, and not vice versa.

Fit Business Intelligence tools to the user and the different roles they play.

Monitor Usage - Shows effectiveness of a Business Intelligence environment and training programs to monitor usage.

lessons learned29
Lessons Learned

Tool of choice for many power users and managers.

Excel can be a legitimate Business Intelligence tool when used as a front end to an analytic server.

Business Intelligence vendors are now embracing Excel and other Microsoft Office tools.

Greatly aids BI standardization efforts.

lessons learned30
Lessons Learned

Don’t deploy Business Intelligence in a haphazard manner

Management wants consistency across departments, reports, and measures to facilitate communication and decision making.


Expectation Management / Communication

Convince people to think strategically



Maintain Support

Scope and Project Management


Individual Resistance To Change

Departmental Autonomy

Long Switching Time And Resources (users)

Executive Sponsorship / Support

Negotiating Pricing With Vendors

  • Data Quality:
    • Issues from source systems
    • Lack of consistency
    • Fragmentation – many sources
    • Reliability
next steps
Next Steps
  • Create a plan to train SUNY users
    • Server Architect
    • Repository/Meta Data
    • Dashboard/Report Development
    • Dashboard User
  • Provide Campuses with BI Support – BI Compentency Center
    • SUNY BI User Group
      • Confluence site
    • Banner ODS/EDW Repository Development
    • Banner ODS/EDW Dashboard/Report Development
    • Library
    • Distance Learning Center
    • Campus access to System Admin BI Dashboards
next steps35
Next Steps
  • Develop SUNY BI best practices
  • Work with Campuses to adopt standards for BI reporting
  • Work towards Shibboleth/Trusted Federation to provide single sign on for BI SUNY wide.
  • Begin to convert existing DW reporting into BI environment
dashboard concept
Dashboard Concept
  • Personal Dashboard (My Dashboard)
  • Shared Dashboards
  • Training helpful, but not required
  • Multiple requests per dashboard
  • Can group requests as we design
    • by functional office (Finance)
    • content area (Cohort)
    • by interest (Community College Data)
  • Ad Hoc Reporting Tool
  • Provide ‘power users’ with ability to access data directly
  • Requires basic training (1 day)
obiee components
OBIEE Components

Delivers. Schedules queries to run on specific cycles. Can be used to trigger alerts. An alert can be created that will notify the user through delivery options, such as email or cell phone.

Disconnected Analytics Oracle BI Disconnected Analytics allows you to view analytics data, Oracle BI Interactive Dashboards, and queries when you cannot connect to the network to access the Oracle Business Intelligence application.

BI Publisher offers a reporting solution available for complex, distributed environments. It provides a central architecture for generating and delivering information—securely and in the right format.

administration tool
Administration Tool
  • Repository Development
  • Technical users
  • Requires Training
  • Provides a rich assortment of tools to enable access to DW stars and Relational or ODS environments.
  • Security Administration
demo questions thank you

Demo & Questions ?Thank you

AIRPO Conference

Presented by : Helen Ernst