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Agile Enterprise Data Management: Terms, Models, Universal Warehouses. Phasic Systems Inc www.phasicsystemsinc.com 703-945-1378. Phasic Systems Inc Management. Geoffrey Malafsky, Ph.D , Founder and CEO Research scientist

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agile enterprise data management terms models universal warehouses

Agile Enterprise Data Management: Terms, Models, Universal Warehouses

Phasic Systems Inc

www.phasicsystemsinc.com

703-945-1378

phasic systems inc management
Phasic Systems Inc Management
  • Geoffrey Malafsky, Ph.D, Founder and CEO
    • Research scientist
    • Supported many organizations in their quest to access the right information at the right time
  • Tim Traverso, SVP Federal
    • Former Technical Director, Navy Deputy CIO
  • Kevin Moran VADM (Ret), COO
    • Former Deputy Chief of Naval Personnel
  • Marshall Maglothin, SVP HealthCare
  • Deborah Malafsky SVP Business Development
our agile methods
Our Agile Methods
  • Why be Agile?
    • Provide flexibility and adaptability to changing business needs while maintaining accuracy and commonality
    • Segmented approach is too slow, rigid, and costly
  • How?
    • Treat data lifecycle as one continuous operation from governance to modeling to integration to warehouses to Business Intelligence
    • Emphasize value produced at each step and overall coordination
    • Seamlessly fit with existing organization, procedures, tools but add Agility, commonality, flexibility, and reduced cost and time
  • We are Agile and comprehensive
    • Typical 60-90 day engagement
    • Deliver completed products not just plans or partial results
methods and tools
Methods and Tools
  • DataStar Discovery: Agile system modeling, data modeling, data semantics
    • Policy, governance, standards and design
    • Fully integrated metadata: each element, table includes attributes for business, IT, and BI
    • Point-select data models, codes, rules, in Data Lifecycle Model
    • Easily build common term standards using all variations with clear understanding of business use scope, meaning
    • Rapid collaborative agreement; line-of-sight to operations
  • DataStar Unifier: Agile Implementation
    • Agile warehousing and aggregation
    • Simplified, common semantics using Corporate NoSQL™
    • Aggregate data using all use case and system variations simply and easily into standard or NoSQL databases
    • Universal warehouse with flexibility, extensibility, adaptability
slide5

PSI Customer Testimonial: VADM (ret) J. “Kevin” Moran

“As a COO of a Wall Street firm and a former US Navy Vice Admiral in charge of a large integrated organization of thousands of people and numerous IT systems, I have seen firsthand the critical role that high-quality enterprise data plays in day-to-day operations of an organization. Without timely access to reliable and trusted data all of our operations were vulnerable to poor decision making, weak performance, and a failure to compete. With Phasic Systems Inc.’s agile methodology and technology, we were finally able to solve our data challenges at a fraction of the time, cost, and organizational turmoil that all the previous and more expensive, time-consuming approaches failed to do.”

agility across the data life cycle
Agility Across the Data Life Cycle

Traditional

►Slow (9-24 months)

► Fractious (business,

IT, BI)

► Expensive

► Inflexible

► Poor practical

semantic mapping

Products

►Data models (all)

► Unifying, concise Data System Model

► Glossaries

► Codes

►Semantic mapping (data, XML,

Legacy, SOA)

► Feed MDM, BI

► Universal Data Warehouse

►Managed governance – integration - analytics

Agile EDM

►Fast (1-3 months)

► Coordinated (business, IT, BI)

► Large decrease $

► Flexible (daily)

► Easy, adaptive

semantic mapping

agile overcome hurdles
Agile: Overcome Hurdles
  • Group rivalry
    • Embrace important business variations; recognize no valid reason to force everyone to use only one view exclusively.
  • Terminology confusion
    • Use a guided framework of well-known concepts to rapidly identify, and implement variations as related entities.
  • Poor knowledge sharing
    • Use integrated metadata where important products (business models, data models, glossaries, code lists, and integration rules) are visible, coordinated, and referenceable
  • Inflexible designs
    • Use a hybrid approach (Corporate NoSQL™) for Agile warehousing and integration blending traditional tables and NoSQL for its immense flexibility and inherent speed
data meaning not just metadata
Data Meaning Not Just Metadata

Governance

Integration

CEO/CFO/CIO

SAP/IBM/ORACLE

Design

MDM

Sales, Accounting

Ontologies

Must be agile in order to adapt quickly to new business needs

  • Continuous change is norm: requirements, consolidation
  • We must use all the important business variations of key terms (e.g. account, client, policy) – No such thing as single version for all!

Which Value? Whose?

My “customer” or your “customer”?

How is data used?

real estate listing example
Real Estate Listing Example
  • Seems simple and well-defined
    • Each house has a type, id, address, etc..
    • Industry standards: OSCRE, RETS
  • Yet, data systems are very different
    • Data model tied tightly to business workflow
    • Extensions and “make-it-work” changes added over time
  • Similar to customer relationship mgmt, ERP, and many other fields
slide11

Main Hurdle to Enterprise Data Standards and Warehouse: Data Values

Not Synchronized with Metadata

Different Meanings (Legal and Business Activities)

NKY HomeSeekers Texas

corporate nosql
Corporate NoSQL™
  • NoSQL gives large systems flexibility & high performance
    • Simple key-value pairs: little data modeling
    • Inherent hardware performance: no database joins (10000x faster)
    • But, poorly suited for corporate use – lacks connection to business
  • Corporate NoSQLTM
    • Blends traditional techniques and NoSQL
    • Tables provide direct alignment to business concepts
    • Key-value pairs eliminate need to delineate every attribute
    • Business driven terminology in production model
    • Easily handles semantic variations
    • Updates do not require changes to data models or physical stores
results
Results
  • Applied to production data:
    • Fully cleaned & integrated data governance approved
      • Requirement: 500,000 records in 2 hrs on Sun E25K
      • Actual: 50 minutes on 3 year low-cost server
  • Governance documents produced and approved
    • Legacy data models – first time in ten years
    • Common data model – directly derived from ontology. Position-Resume model
  • Standing governance board created with short decision-making monthly meetings
    • Position-Resume Governance Board
  • Process approach and technology applied to new IT systems