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Exploring the Value and ROI of Data Architecture

This presentation delves into the world of data architecture, discussing its importance, dos and don'ts, value, performance tuning, and return on investment (ROI). Discover how data architecture adds value and enhances business operations. Learn how to keep yourself employed and expand your role in the field of data architecture.

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Exploring the Value and ROI of Data Architecture

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  1. Data Architecture a passion? A career? Or both? Until you do what you believe in, you don't know whether you believe it or not.Leo Tolstoy

  2. Agenda / Timing • Before the break • The Ideas of Data Architecture • The ROI of Data Architecture • Ideas for keeping yourself employed • After the break • Your own experiences • Tweaking this presentation

  3. Data Architecture (what we are not) • The data management organization is viewed as a group of eccentrics with ersatz skill sets who aren’t nearly as vital to IT as the developers and data base administrators, or worse—viewed as a roadblock Jane Carbone - Infomajic LLC

  4. Data Architecture (what we are) • Business Partners • Data Savvy • Visionaries • Translators • Collaborators • Gate Keepers • Analysts • Integrators

  5. Data Architecture Dos & Don’ts • Be responsive – not ivory tower • Use the business’ terminology • Ask for feedback on the design • Patiently explain what you do • Ask or suggest don’t tell • Be prepared to give simple but clear trade-offs.

  6. Data Architecture ValueNormalizing • Eliminate repeating groups • No non-key attributes depend on a portion of the primary key. • No attributes depend on other non-key attributes.

  7. Data Architecture Valuevs Denormalizing • Intentionally duplicate data • Intentionally create summary data • Split tables into fewer rows • Split tables into fewer attributes

  8. Data Architecture ValueStandardization • Naming • Nomenclature, consistency • Data Dictionary Entries • Conceptual, Logical, Physical Models • Scripting

  9. Data Architecture ValuePerformance Tuning • No matter how much tuning you apply to the DBMS, it cannot compensate for a bad design. • Minimize table joins • Reduce excessive lookup or code tables • Keep key structures simple and numeric where possible • Be deliberate about string data • Identify Temp data and put in separate tables

  10. Data Architecture ValuePerformance Tuning • Speed of Data Load • Not null constraints slows loads • Domain Validation slows loads • Create only needed attributes • vs Query Speed • Denormalize as appropriate • Require Indexes on all Foreign Keys • Partition Large Tables • Make sure PK and not null columns are at front (top) of table.

  11. Data Architecture ROI • ROI is a comparison of benefits to cost expressed as a percentage of the original investment • Bigger isn’t always better or • Less is More • Understanding the Life Time Value of the Customer

  12. Data Architecture ROI ( examples) • Large Insurance Company, reduced $$ in reserves, once they understood the “real” amount they needed. • Current Retail data indicates which profiles of customers are most likely to buy, have bought recently, and project what kinds of products the company needs on hand • The Diaper and Beer analogy • Fraud Detection

  13. Data Architecture ROI (Public Social Systems) • In one East Coast City the average cost for Public housing intervention, decreased from $77,000 to $35,000. • A Virginia city was able to demonstrate the cost savings of keeping children in school, as relates to paying back in taxes rather than being on welfare • An elderly living at home project, was able to demonstrate that helping elderly get transportation averaged $300 per year versus $36,000 per year for institutions.

  14. Keeping your (DA) Job • Keep up your education (all facets) • Develop partnerships with Peers • Keep up networking opportunities like DAMA, DBUG or other professional organizations • Spend time staying business current • When feasible attend training or informational meetings that are peripheral to your job.

  15. Expanding your role • Data Quality Validation • Report Writing using the Company’s favored tool • A little ETL work • Data Digging for Data Dictionary • Project Leader / Planner

  16. In conclusion • Evaluate the place for Data Architecture in your environment • Creatively think of ideas showing ROI / Adding value • Take risks learning new job skills, to compliment your DA Passion.

  17. Questions & Ideas • Dawn Michels • Lead Data Architect • Past Pres DAMA MN • Past VP Chapter Services DAMAI • Adjunct Faculty Member College of St. Catherine • dawnmichels@fairisaac.com • 651-486-4626

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