modeling big data with the archimate 3.0 language
TRANSCRIPT
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Modeling Big Data with the ArchiMate 3.0 Language
Iver BandOpen Group Conference, Austin, TexasJuly 19, 2016
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Agenda•Background•A Foundation for Modeling Big Data Architectures•Fitness Tracker Analytics Case Study•Conclusion
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BACKGROUND
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Iver Band
• Enterprise Architect at Cambia Health Solutions
• Consumer and group data, web services architecture
• Architecture methods and tools
• Vice Chair, Open Group ArchiMate Forum• ArchiMate 3.0 standard and related white
papers
• TOGAF and ArchiMate certified, CISSP, AHIP Certified IT Professional, Certified Information Professional
• ArchiMate user since 2010
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About Cambia
22 companiesand growing
© 2016 Cambia Health Solutions, Inc.
A tax-paying nonprofit headquartered in
the Pacific Northwest
Nationally recognized: Top 100 Healthiest
Workplaces
5,300 employeesin 30 states
100 million people touched nationwide
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Cambia Health Solutions
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SeniorServices
HealthInsurance
RetailEnablement
ProviderEnablement
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A FOUNDATION FOR MODELING BIG DATA ARCHITECTURES
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What is Big Data?• Consists of datasets that cannot be handled efficiently with traditional data architecture.
• These datasets have extensive
• Volume – Size of dataset • Variety – Multiple repositories, domains, or types• Velocity – Rate of flow• Variability – Rate of change in other characteristics
• These characteristics require a scalable architecture for efficient, storage, manipulation and analysis
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Adapted from NIST SP1500-1 Big Data Interoperability Framework: Volume 1: Definitions
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Why is Big Data Important to All Enterprise and Solution Architects in Healthcare?
• Social, mobile, analytics, cloud, and Internet of Things technologies, including connected health devices (CHDs), produce huge volumes of data and enable continuous analysis
• Health Care organizations gather data from sources such as electronic medical records, payer systems, and CHDs.
• Health Care organizations derive insights from data to make their services more effective, efficient and accessible.
• Gartner estimates that 90% of large organizations will have a chief data officer by 2019*
• Therefore, Health Care Enterprise and Solution Architects need to consider building or integrating Big Data capabilities throughout their work
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*January 26, 2016 press release. http://www.gartner.com/newsroom/id/3190117
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Why Are Standardized Architectural Frameworks Important to Big Data?
•Big Data solutions• Combine theory, technologies, and methods from multiple fields• Combine data from multiple parts of the enterprise• Impact a wide range of disciplines• Require interoperability across multiple organizations
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What Does the ArchiMate Standard Provide?
• A language with concepts to describe architectures
• A framework to organize these concepts
• A graphical notation for these concepts
• Guidance on visualizations for different stakeholders
• An open standard maintained by The Open Group
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The ArchiMate 3 Framework
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Strategy
Implementation& migration
Physical
Application
Technology
Business
MotivationPassivestructure
Behavior Activestructure
Aspects
Laye
rs
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Correspondence Between the ArchiMate 3 Framework and the TOGAF Architecture Development Method
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NIST Big Data Interoperability Framework
• Product of working group “to develop consensus on important, fundamental concepts related to big data”
• Three versions1. Reference architecture key components
(published)
2. Interfaces between components (planned)
3. Validation with apps that interoperate through interfaces (planned)
• First version has seven volumes1. Definitions
2. Taxonomies
3. Use Cases and General Requirements
4. Security and privacy
5. Architectures White Paper Survey
6. Reference Architecture
7. Standards Roadmap
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From NIST SP1500-1 Big Data Interoperability Framework: Volume 1: Definitions
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NIST Big Data Reference Architecture (NBDRA)From NIST SP1500-1 Big Data Interoper-ability Framework: Volume 6: Reference Architecture
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NBDRA Overview:Roles and Capabilities
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NBDRA Big DataFramework Capabilities with Resources
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FITNESS TRACKER ANALYTICS CASE STUDY
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Fitness Tracker Analytics Motivations
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Fitness Tracker Analytics Project Assignments to NBDRA Roles
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Fitness Tracker Analytics Data Processing
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Introduction to MapReduce
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Claims Data Processing with MapReduce
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Claims Data Processing TechnologyWith ResourceRealization
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Fitness Tracker Analytics Implementation & Migration
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CONCLUSION
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Conclusion• Big Data challenges are distinguished by the Volume, Velocity, Variety, and Variability of the data that they must handle
• All Enterprise Architects should consider including Big Data capabilities in their architectures
• The NIST Big Data Reference Architecture provides a common framework for a broad range of Big Data solutions
• The ArchiMate language can be used to model Big Data strategies and the solutions that realize them
• The ArchiMate 3.0 language, with its new Strategy Elements, additional Application Layer concepts, and increased ability to express complex models, is particularly well suited for Big Data modeling
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References
• ArchiMate Language www.opengroup.org/archimate • NIST Big Data Reference Architecture http://www.nist.gov/itl/bigdata/bigdatainfo.cfm• Speaker [email protected]• More presentations like this http://slideshare.net/iverband