Post on 17-Dec-2018
Business Intelligence for the Modern Utility
Presented By:
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Presented By: Glenn Wolf, CISSP (Certified Information Systems Security Professional)
Senior ConsultantWestin Engineering, Inc.Boise, IDSeptember 15th, 2009 8:00-8:40am
Agenda
• Introduction• Performance Management• Challenges of Data Management for Decision Support• Transaction Processing vs. Business Intelligence Systems• Business Intelligence and Service Oriented Architectures• Benefits of Business Intelligence• Business Intelligence Applications• Dashboards vs. Scorecards• Business Intelligence Trends and Products• Secure Data Transfer from SCADA and Other Systems• Critical Success Factors• Next Steps
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Introduction
• Business Intelligence:The skills, technologies, applications and practices used to help a business (or organization) acquire a better understanding of its commercial context.
• Common Business Intelligence Applications• Spreadsheets, Ad-hoc Query Tools• Spreadsheets, Ad-hoc Query Tools• Reporting, Analysis (OLAP)• Dashboards / Scorecards• Data Mining / Predictive Analysis
• Business Intelligence Data Sources• Raw Source Systems (OLTP)• Data Warehouse / Data Mart / Operational Data Store (ODS)• Optimized BI Server Cache• Flat Files / Data Extracts
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Performance Management
DevelopAppropriateMeasures and
Targets
DevelopAppropriateMeasures and
Targets
Routinely Monitor
the Results
Routinely Monitor
the Results
Analyze Results againstTargets
Analyze Results againstTargets
CommunicateResults to
Stakeholders
CommunicateResults to
Stakeholders
ImplementAppropriateCorrectiveActions
DevelopBusinessStrategiesand Goals
Performance Reporting Process
DevelopAppropriateMeasures and
Targets
DevelopAppropriateMeasures and
Targets
Routinely Monitor
the Results
Routinely Monitor
the Results
Analyze Results againstTargets
Analyze Results againstTargets
Results toStakeholders
CommunicateResults to
Stakeholders
ImplementAppropriateCorrectiveActions
DevelopBusinessStrategiesand Goals
Decision Support
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• Are we achieving our mission?
• Are we achieving our vision?
• What is our actual performance against desired targets?
• Are we continuously improving?
• Are we effectively communicating the results?
ActionsActions
Challenges of Data Management forBusiness Intelligence
• Many disparate systems (“silos”) – too much data, not enough information.
• Lack of integrated systems
• Proprietary database systems or data models.
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• Aggregation and reporting confined within each system.
• Reporting is cumbersome and slow, and often affects operational systems (slow-downs and crashes).
• Too many people using spreadsheets coming up with different answers to the same questions.
Transaction Processing Systems vs. Business Intelligence Systems
• Transaction Processing Systems• Highly optimized for specific business areas
• High frequency of quick updates and quick retrieval
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• Data is real-time
• Record-locking and query caching issues
• Servers need fast CPU, fast I/O (disk, network)
• Databases are highly normalized (broken down)
Transaction Processing Systems vs. Business Intelligence Systems
• Business Intelligence Systems• Highly optimized to aggregate data from many sources; data
aggregated into “cubes” built around subject matter interests
• Large bulk queries only; optimized to address sorting and grouping issues
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grouping issues
• Data is not real-time
• Servers need fast CPU, lots of memory, lots of disk space
• Metrics are pre-computed and management-approved
Business Intelligence and Service Oriented Architectures
• The Old Way• Self-contained, standalone BI applications• “Mish-mashed” infrastructure of acquired, force-
integrated platforms• Monolithic BI technologies, loosely integrated via
proprietary standards
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• Legacy architectures and proprietary licensing models
• The New Way• Componentized and modular• Service-implemented architecture
• Built “from the ground up” as a set of services• Exposed via AJAX and Web Services• Commitment to a standards-based architecture
and adoption-friendly licensing model
Business Intelligence:Benefits
• Support Performance Improvement Initiatives.
• Provide sustainable support for business processes through automation.
• Reduce staff time associated with report generation and production.
• Support data quality improvement initiatives and overall data
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• Support data quality improvement initiatives and overall data governance.
• Drive “one version of the truth.”
• Enable more timely (and accurate) decision making.
Business Intelligence Systems:A Different Kind of Data Management
Core UtilityApplications
Finance / HR
Budgeting
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Budgeting
Purchasing
Project Management
Maintenance Mgmt.
LIMS
SCADA
PIMS
CAD
Business Intelligence Systems:A Different Kind of Data Management
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Business Intelligence Systems:A Different Kind of Data Management
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Business Intelligence Systems:A Different Kind of Data Management
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Utility Intelligence Applications: Providing Information for Decision Making
PerformancePerformanceDashboards & ScorecardsDashboards & Scorecards
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SupervisorsSupervisors DepartmentDepartmentHeadsHeads
AnalystsAnalystsGeneral General ManagersManagers
Utility Intelligence Systems:Comparing Technologies
Dashboard Scorecard
Purpose Monitors and measures operational processes
Monitors progress toward established objectives
Data Events, Transactional Aggregates, Consolidation
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Data Events, Transactional Aggregates, Consolidation
Refresh Rate
Near real-time (“latest and greatest”)
Periodic (“snapshots”)
Measures Exceptions linked to operations
Targets linked to strategic plans
Utility Intelligence Systems:Not Mutually Exclusive
Manage
Measure
Measures Progression
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Measure
Monitor
Measures Anything
Utility Intelligence Systems:Comparing Technologies
Dashboard Scorecard
Purpose Monitors and measures operational processes
Monitors progress toward established objectives
Data Events, Transactional Aggregates, Consolidation
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Data Events, Transactional Aggregates, Consolidation
Refresh Rate
Near real-time (“latest and greatest”)
Periodic (“snapshots”)
Measures Exceptions linked to operations
Targets linked to strategic plans
Performance Dashboards:Monitoring Operational Processes
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Utility Intelligence Systems:Comparing Technologies
Dashboard Scorecard
Purpose Monitors and measures operational processes
Monitors progress toward established objectives
Data Events, Transactional Aggregates, Consolidation
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Data Events, Transactional Aggregates, Consolidation
Refresh Rate
Near real-time (“latest and greatest”)
Periodic (“snapshots”)
Measures Exceptions linked to operations
Targets linked to strategic plans
The Balanced Scorecard:A Framework for Monitoring Progress
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Objectives Measures Targets Initiatives
Performance Scorecards:Drilling Down
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Business Intelligence Products:Software Tools with Different Capabilities
Complex
Develo
pment
Tools
Simple
Develo
pment
Tools
Web
Access Tools
Business Objects SAS Web Report StudioPentaho BI
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• Rulers
• Relative Object Placement
• Programmatic control of layout and formatting
• Multiple grids & graphs
• Highlight exceptions
• Easily position objects on page
• Mixed grid / graph
Crystal ReportsHyperion Production Reports (SQR)Microsoft Reporting Services
Cognos Report StudioMicroStrategy Report Services
IBI Web Focus
Business ObjectsWeb Intelligence
HyperionInteractive Reports
SAS Web Report Studio
MicroStrategy Web
Cognos Query Studio
Pentaho BIJaspersoft
Business Intelligence:Key Trends
• Wide Variety of Software Tools – addressing the needs of different user groups
• Software Vendor Consolidation – only a few vendors remaining, including the big ones (Microsoft, IBM, SAP)
• BI Software Suites – buyers want integrated toolsets
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• BI Software Suites – buyers want integrated toolsets
• Open Source BI – solid market presence due to ease of integration
• Continuous Improvement - Strong links to Performance Management
The Benefits of BI Suites
• Business flexibility• Extensive features and functionality built in• Improved cost-benefit ratio
• Reduced complexity• Pre-Integrated Components• Vendor commitments to enhancements
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• Vendor commitments to enhancements• Streamlined design and implementation
• Additional benefits of open source BI• Lower costs• Lower upfront costs – pilot projects more feasible• Extensive community of experts• Pre-integrated components from the ground up• Future plans fully communicated
Secure Data Transfer from SCADA and Other Systems
• SCADA should be on its own network• Create DMZ (DeMilitarized Zone) between SCADA and
IT networks• SCADA network “pushes” data to copy of servers in the DMZ• IT network users can access server copies in DMZ
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• IT network users can access server copies in DMZ• No access from IT network to SCADA network• If a DMZ server is compromised, intruder is stuck there
• Monitor interconnections and access points with Network-based Intrusion Detection System (NIDS)
Business Intelligence Implementation:Critical Success Factors
• Provide the technical basis for the BI environment• Servers, network connectivity, data source accessibility• Scalability, reliability
• Identify and define the data• Data sources – databases and/or manual inputs• Data quality and data quality assurance processes
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• Data quality and data quality assurance processes• Data mapping, derivation, transformation, and aggregation according to
requirements and business rules• Data terms defined in business terms (metadata)
• Utilize proven practices for application design and implementation
• Assemble business requirements• Define the applications for queries, reports, and charts• Design the information model
Business Intelligence: Next Steps
• Business Intelligence Needs Assessment
• Start with Pilot Project• Identify the Top Questions that Need Answering• Automate the Most Useful / Time Consuming Reports
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• Phased Rollout• Keep Stakeholders Involved• End-User Training on Tools• Maintain Realistic Performance Targets
Questions
Glenn Wolf, CISSP
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Glenn Wolf, CISSPSenior Consultant, Westin Engineering, Inc.
glenn.wolf@we-inc.com
info@we-inc.comwe-inc.com or westinsolutions.com
Use for Slides Containing Large Graphical Diagrams
Overview
Overview
Overview
Overview
Overview
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Extra pieces for color reference etc.