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DataFlux Data Management Approach Calgary and Edmonton SAS USERS GROUP May 10th and 11th, 2011
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A bit about me…
Office: 403-802-4454
Mobile: 403-828-1547
Marc has been implementing and selling information management, business intelligence and analytics solutions for nearly 20 years in the financial services, communication, retail, government, healthcare, pharmaceutical, energy, and mining and metallurgy industries. Marc has been with SAS for nearly 10 years and is currently a principal Solutions Architect based in Calgary Alberta.
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• The Data Warehousing Institute (TDWI) estimates that data quality problems associated with customer contact data alone cost U.S. businesses more than $600 billion a year in postage, printing and staff overhead. This doesn't include losses from lost revenue, bad decisions and missed opportunities…or losses from other types of bad data.
• A study of 599 businesses by PricewaterhouseCoopers led them to estimate that bad data is costing businesses $1.4 billion a year in accounting, billing and inventory snafus.
Why worry?
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Data Governance Maturity Model
Sales Force
Automation
Database Marketing
EMR
IT-driven projects
Duplicate,
inconsistent data
Inability to adapt to
business changes
Data Warehouse
ERP
CRM
Hospital
Line of business
influences IT projects
Some cross-functional
collaboration
High cost to maintain
multiple applications
IT and business
groups collaborate
Enterprise view of certain
domains
Data is a corporate
asset
Business
requirements drive IT
projects
Repeatable, automated
business processes
Personalized customer
relationships and
optimized operations
Customer MDM
Patient MDM
Employee MDM
Location MDM
MDM
Business Process
Automation
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Data Governance
Data Management
Data Governance vs. Data Management
Executive Leadership Team
DG Executive Sponsor
Data
Modeling
Data Owners
Data
Administration
Master Data
Management
Data
Quality
Data Owners Data Owners
Data Steward Data Steward Data Steward
Data Owners
Data
Integration
Privacy and Security
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Your Data. Your Business. One Solution.
DataFlux enables business agility and IT efficiency by providing innovative data management technology and services that transform data into a strategic asset.
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The Business Drivers of Data Quality
7
• Customer Acquisition, Satisfaction and Loyalty
• Business Agility
• Revenue / Performance Enhancement
Increase Revenue & Performance
• Modernization
• Productivity
• Supply Chain Optimization
Optimize Operations
• Safety
• Risk Mitigation
• Compliance
Governance, Risk and Compliance
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DataFlux Data Management Framework provides all the necessary components for data management success.
One Solution
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Why DataFlux?
Gartner Magic Quadrant for
Data Quality Tools, 2010
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DataFlux Federation Server
Virtual access On-demand data
integration
DataFlux Data Management Studio
Define Discover Design Execute Evaluate Control
DataFlux Data Management Platform
DataFlux Data Management Server
Real-time/ transactional
Bulk/batch
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Data Management Lifecycle Methodology
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DataFlux Demo
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Business Process Automation
Data Management Platform
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• Guided, proven methodology for data quality, data integration, and MDM
• Focused experience in delivering multi-phase, progressive data management initiatives
• Technology built for positive user experience … and today’s business problems
• Roadmap for the future, grounded in data governance and focused on enterprise data management
Benefits of the DataFlux Approach
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Opening screen DataFlux Data Life Cycle embedded in software
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DataFlux Data Life Cycle
– Explore metadata to ensure that the right data sources are included in the data management program
– Create detailed data profiles of identified data sources to understand strengths and weaknesses of data prior to the start of the project
– Apply business rules to the data to test which sources are out-of-limits with existing business standards
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Plan Phase - Discover
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Data Management Studio
– Explore • Relationships within and across systems
• Identify content of fields
– Profile • Structure and quality of data
• Gain a better understanding of your organization’s data assets
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Discover
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Data Management Studio
– Explore • Relationships within and across systems
• Identify content of fields
– Profile • Structure and quality of data
• Gain a better understanding of your organization’s data assets
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Discover
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Data Management Studio
– Business Rules • Create and Manage Rules
– Data Management • Define and manage schemas
• Native DBMS type support
• “ELT” based data manipulation (i.e. In-Database Processing)
– Process Modelling • Parallel Processing Orchestration
• Conditional Execution
• Event Triggering
• Create, start, run workflows
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Design
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Data Management Studio
– SAS nodes to Write & Execute SAS Code
– Orchestrate SAS DI Studio Jobs
– Use SAS scoring within Data Management Studio
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Integrate SAS jobs
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Data Management Studio
– Execute • Install business rules within the IT
infrastructure
• Determine integration method – real-time, batch or virtual
• Reuse and redeploy the same set of business rules across applications, helping increase data consistency in the enterprise
– Review results • Exception handling (eg. handling
specific duplicates that require manual inspection)
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Execute
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Data Management Studio
– Define and enforce business rules to measure the consistency, accuracy and reliability of new data as it enters the enterprise
– Create reports and dashboards on critical data metrics for key business and IT staffs
– Use information from data monitoring reports to refine and adjust business rules
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Evaluate
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Data Management Studio
– Define and enforce business rules to measure the consistency, accuracy and reliability of new data as it enters the enterprise
– Create reports and dashboards on critical data metrics for key business and IT staffs
– Use information from data monitoring reports to refine and adjust business rules
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Evaluate
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