The 2013 Computerworld Honors Laureate

1. LTC Bobby Saxon Division Chief, US Army G-3/5/7 Twitter: @BobbySaxon LinkedIn: Bobby Saxon The 2013 Computerworld Honors Laureate 2013 Top 20 Innovations that Mattered Innovation Award Winner 2013 Federal IT Program of the Year

2. EMDS Mission Mission Manage the retrieval and integration of disparate data & processes to create an automated common access point for holistic and detailed Army data in order to enhance understanding and decision making

3. Why EMDS? • Stove-piped / legacy systems with vast data • Near real-time access required • Lack of standards = inaccuracies / inconsistencies • Not all systems are “total Army” • One Question = One Answer • Evolving Strategic Predictive Analysis needs This led to a requirement for an IT system (EMDS) that evolved into a Big Data system

4. What is Big Data Source: Datameer.com

5. What is Big Data Source: Jeffhurtblog.com

6. What makes Big Data Possible • Moore’s Law - Computing power doubles every two years • Kryder’s Law - Storage capacity increasing / cost decreasing faster than Moore’s Law • Butter’s Law – Amount of data coming out of optical fiber is doubling every nine months • Nielsen’s Law – Network connection speeds for high-end home users increase by 50% yearly

7. “Expert” definitions of Big Data A new generation of technologies and architectures designed to extract value economically from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. (IDC) A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. (SAS) Describes the exponential growth, availability and use of information, both structured and unstructured. (Wikipedia) Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make your business more agile, and to answer questions that were previously considered beyond your reach. (IBM) High volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. (Gartner) Big Data is an organization’s ability to store, process, and access all the data it needs to operate effectively, make decisions, reduce risks, and serve customers. (Forrester) A situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making (SAS)

8. EMDS definition of Big Data A new generation of technologies and architectures designed to extract value economically from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. (IDC) A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. (SAS) Describes the exponential growth, availability and use of information, both structured and unstructured. (Wikipedia) Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make your business more agile, and to answer questions that were previously considered beyond your reach. . (IBM) High volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. (Gartner) Big Data is an organization’s ability to store, process, and access all the data it needs to operate effectively, make decisions, reduce risks, and serve customers. (Forrester) A situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making (SAS)

9. EMDS

10. EMDS Overview • Senior Leader decision support tool • Retrieves and integrates disparate data • Common access point for holistic/detailed data • SIPRNet based and web-enabled • Readiness, Resourcing, and ARFORGEN • Total Army – 10K / 70K, 1.1M, 3600+ IT Access + Understanding = Discovery

11. Data Access HQDA Leaders G-37 FM G-4 FC G-35 SS G-33 OD AMC G-8 Resourcing, Trending & Projections CDRs ARFORGEN Readiness ARNG G-3 1 2 3 4 Joint Staff SRUs Decision Support Capability Common Operating Picture Force Structure (AOS) Other G-1 G-3 FM G-3 TR G-3 OD G-4 (incl. AMC) G-8 ACSIM ARNG & USAR (LIW & AST) (COPS, DMDC & PAM XXI) (SAMAS / DRRS-A) (TAMIS) (DRRS-A & MDIS) (LEXIS) (AE2S) (RPLANS / ISR / ASIP) (ITAPDB-G / TAPDB-R, & AREM) In Progress

12. Data Understanding • Snapshot of historic, current, and projected force structure • Visual portrayal of previously difficult to access and understand data

13. Data Discovery

14. Lessons Learned • “Traditional data skills” are not “Big Data skills” • Technology is important… People are critical • Manage expectations • Push back • Embrace agility • Be Visionary

15. Way Ahead • Predictive Analytics • Department of Defense / Army • Strategic Readiness • Intelligence • Suicide Mitigation • Commercial Examples • eHarmony • Money Ball • Progressive Insurance “The potency of prediction is pronounced – as long as the predictions are better than guessing” Eric Siegel Predictive Analytics

16. I’ll leave you with… “Getting value from Big Data is like mining for Gold. You go through a lot of dirt to find the Nuggets” @BobbySaxon

17. LTC Bobby Saxon Division Chief, US Army G-3/5/7 Twitter: @BobbySaxon LinkedIn: Bobby Saxon The 2013 Computerworld Honors Laureate 2013 Top 20 Innovations that Mattered Innovation Award Winner 2013 Federal IT Program of the Year