Transcript SUNY Business Intelligence Initiative

Business Intelligence Initiative
AIRPO Conference
June 18, 2008
Presented by : Helen Ernst
[email protected]
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 tuned
for easy access and use by information
consumers and analysts, especially for the
purpose of decision making.
What is ‘Business Intelligence’ software?
A set of concepts and methods to improve
business decision making by using factbased 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).
Analytic Culture
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 decisionmaking processes at SUNY.
Strategy
Strategy
Planning
Mission, Goals,
Strategy ->Defining
measurable outcomes
(KPI)
Budgets, Plans,
Forecasts, Models ->
Set Targets
Integrated
Act/Adjust
Information
Alerts -> Actions,
Decisions, Adjust
plans
Monitor/Analyze
Dashboards
Business
Intelligence
Execution
Transactional vs.. Analytical Systems
Operational/Transactional
1.
2.
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7.
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.
Analytical and Reporting
1.
2.
3.
4.
5.
6.
7.
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
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
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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
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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.
Proof of Concept Projects
SUNY Proof of Concepts
• UB: Strategic Information Reporting Initiative (SIRI)
– Contact: Joe Kerr [email protected]
• OSA: University Business Intelligence Data
Management
– Contact: Helen Ernst [email protected]
• OSA: Banner Reporting and Analytics
– Contact: Ron [email protected]
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 Projects
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 Projects
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
• 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 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 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
– Integrate with Single Sign-on
– Use Initialization Blocks (Queries)
– Session Variables & Header Records
– Longer Term Vision, Shibboleth Identity &
Federated Model
Lessons Learned
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 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 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 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 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 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 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 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 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 Learned
• Don’t deploy Business Intelligence in a haphazard
manner
• Management wants consistency across departments,
reports, and measures to facilitate communication
and decision making.
Challenges
• Expectation Management /
Communication
• Convince people to think strategically
• Politics
• Culture
• Maintain Support
• Scope and Project Management
Challenges
• Individual Resistance To Change
• Departmental Autonomy
• Long Switching Time And Resources
(users)
• Executive Sponsorship / Support
• Negotiating Pricing With Vendors
Challenges
• Data Quality:
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Issues from source systems
Lack of consistency
Fragmentation – many sources
Reliability
Next Steps
• Create a plan to train SUNY users
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Server Architect
Repository/Meta Data
Dashboard/Report Development
Dashboard User
• Provide Campuses with BI Support – BI Compentency Center
– SUNY BI User Group
• Confluence site
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Banner ODS/EDW Repository Development
Banner ODS/EDW Dashboard/Report Development
Library
Distance Learning Center
Campus access to System Admin BI Dashboards
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
Oracle Business Intelligence
Enterprise Edition
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)
Answers
• Ad Hoc Reporting Tool
• Provide ‘power users’ with ability to
access data directly
• Requires basic training (1 day)
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
• 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
AIRPO Conference
Presented by : Helen Ernst
[email protected]