Reducing Risk through Improved T&E Knowledge Management · value –Example: If the ... that rapidly answer questions and discover “unknown unknowns” ... • By embracing KM &

UNCLASSIFIED ndash DISTRIBUTION STATEMENT A

Reference Number 14-S-2600 September 30 2014

Reducing Risk through Improved TampE

Knowledge Management

Ryan Norman

TRMC Initiative Lead for Knowledge Management

ATampL Test Resource Management Center

ryantnormancivmailmil

2UNCLASSIFIED ndash DISTRIBUTION STATEMENT A Reference Number 14-S-2600

DASD(DTampE) Director TRMC

Staff DirectorLt Col Brian Bohenek

USAF

Principal Deputy DTampE

Vacant

(SES)

DASD(DTampE) Director TRMCDr C David Brown

Principal Deputy Director TRMC

Mr Derrick Hinton

(SES)

bull Monitorreview DTampE activities of

major defense acquisition programs

bull Develop Policy and Guidance

bull Assist Program Offices (Chief

Developmental Testers) in TampE

Planning

bull Test amp Evaluation Master Plan

(TEMP) approvaldisapproval

bull Advocacy for Acquisition DTampE

workforce

bull Annual Report to Congress

bull Steward of the DoD test and

evaluation (TampE) infrastructurendash Major Range and Test Facility Base (MRTFB)

bull Services TampE budget certification

bull TampE Infrastructure Investmentsndash TampE Science and Technology (SampT) Program

ndash Central Test and Evaluation Investment

Program (CTEIP)

ndash Electronic Warfare Infrastructure

Improvement Project (EWIIP)

ndash Joint Mission Environment Test Capability

(JMETC) Program

ndash National Cyber Range (NCR)

bull Biannual Strategic Plan to Congress

DTampE TRMC


TRMC Knowledge Management (KM) Recent Efforts

bull (FY12) Completed Data Management for Distributed Testing

(DM-DT) Study

ndash Result Developed functional requirements for TampE Enterprise Data

Management

bull (FY13) Comprehensive Review of TampE Infrastructure report

published ndash aka ldquoThe TampE Infrastructure Study

ndash Key Recommendation Use DoD cloud solution for TampE data

ndash Key Recommendation USD(ATampL) establish a DoD-wide KM capability for

TampE to help achieve better acquisition outcomes and reduce costs

bull (FY1415) JMETC Program Element (PE) increasing to support

cyber TampE requirements

ndash Includes funding to establish Regional Service Delivery Points

bull (FY14) Joint Strike Fighter Knowledge Management (JSF-KM)

project initiated

ndash Goal Assess KM technologies and methodologies with an existing acquisition

program to inform an enterprise approach to TampE knowledge management


What is Knowledge Management (KM)

bull Data represents a fact or statement without relation to other

things

ndash Example It is raining

bull Information is data that has been placed in a meaningful

context

ndash Example The temperature dropped 15 degrees amp then it started raining

bull Knowledge is a collection of information with some extracted

value

ndash Example If the humidity is very high amp the temperature drops substantially the

atmosphere is often unlikely to hold the moisture ndash so it rains

bull Knowledge Management (KM) is the process of efficiently

capturing handling distributing and using knowledge

bull KM is based on two critical activities

ndash The capture amp documentation of explicit amp implied knowledge

ndash The dissemination of this knowledge within an organization(s)

The TampE mission is to attain and share knowledge



RDTampE Live Virtual Constructive (LVC) ldquoLayersrdquo

Knowledge Management Layer

Operational Capability Layer (LVC)

Test Resource Layer (LVC)

Test

Resource

Data

Loggers

Operational

Capability

Data

Loggers

Layer Interface(s)

Data Retrieval

Analysis

Presentation

No

n-ldquo

Re

al-

Tim

erdquo D

ata

Tra

ns

fer Layer Interface(s)

Real-Time Post-Test

Processing

Generates TampE

Data

Captures TampE

Data

Where Data

becomes

Knowledge



TampE Data Levels in the Knowledge Management Layer

6

Level 1 Raw Data

Level 2 Reduced Data

Level 3 Ordered Data

Level 4

Findings Summary Statistics

Level 5

Analysis Inferential Statistics

Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ

Bulk of data is not delivered to customers and is not preserved



Keys to an Effective Knowledge Management Approach

bull Trusted processes across government and industry that identify

acquisition problems sooner rather than later

ndash Result Develops mutual trust in testing products

bull Accessibility of knowledge amp data to legitimate users

ndash Result Efficiencies gained through reducing the amount of testing required to

obtain knowledge

bull Discoverability of knowledge amp data obtained over time

ndash Result Enables data scientists to leverage data mining and analytical tools

that rapidly answer questions and discover ldquounknown unknownsrdquo

bull Availability of knowledge through common tools amp technologies ndash

Example Cloud storage and services

ndash Result Efficiencies gained from readily available amp shared technology

hardware software and processes

Primary Goal of TampE Discern Knowledge from Collected Data



User

Long-term DoD TampE Enterprise Knowledge Management

8

Result TampE data used more effectively amp efficiently in support of acquisition

bull True product of TampE should be data amp knowledge

bull TampE data currently compartmentalized with little

discovery or reuse outside of program

bull By embracing KM amp Big Data Analytics DoD can efficiently handle amp securely share TampE data

bull KM will enable all TampE data to be usable to build knowledge across all DoD acquisitions

bull Distributed data repositories will enable execution amp automated search scenarios that cannot occur today

Savings

bull Fewer Tests Planned bull Reduced Software Licenses

bull Eliminates Duplicative Custom Tools bull Reduced Information Assurance Expenses

bull Continuous Regression Testing

bull Improved Preventative Maintenance

bull Fewer Duplicative DT and OTbull Access to Historical Data wo

Buying it from the Prime

bull Identification of Shared Issues

w Other Systems

bull Faster Root Cause Analysis

Avoidancebull Data Available for Leverage by Shared

Systems

bull Pre-flight checkout of SUT and Instrumentation

bull MampS of test mission parameters

bull Data trend analysis leads to predictive failure alerts

Test Planning

Test Setup

Data Analysis amp Evaluation

System Fielding

bull Fewer Test Hours Spent Chasing Previously Identified Issues

bull Increased Data Harvesting Speed

bull Find amp Fix Problems Faster

TampE Knowledge Management Cost Efficiencies

bull Reduced TDY

bull Reduced Diagnostic Time for Issues

bull Automated ldquoUnknown Unknownrdquo Issue Identification

9UNCLASSIFIED ndash DISTRIBUTION STATEMENT A



Joint Strike Fighter Knowledge Management (JSF-KM) Effort Overview

bull TRMC is investigating tools techniques resources policies amp

procedures needed to more efficiently amp effectively use TampE data

bull TRMC is partnering with Joint Strike Fighter (JSF) to ascertain

how Big Data tools amp Cloud Computing technologies could assist

acquisition programs during TampE

bull TRMC will establish a next-generation Knowledge Management

(KM) capability that utilizes the latest in virtualization

technologies methodologies amp best practices for JSF OT data

bull Capability will enable remote search amp retrieval of JSF OTampE data

10

JSF JPO is assisting TRMC in prototyping

a Big Data Enterprise KM system



User

Eglin

Pax

River

JSF-KM Test Concept

bull DT amp OT data storage in government facilities

bull Collect Store ldquoDT qualityrdquo data during OT

bull Search Analyze Edwards amp Nellis

data from any secure location

bull Brings enhanced JMETC infrastructure to JSF TampE

bull Knowledge shared across

JSF DT OT TampE locations

bull Apply commercial

technologies to DoD requirements

bull Scalable to other JSF TampE locations

11

JPO

Pote

ntia

l Expansio

n



TampE Data Analytics for Improving Operationally Fielded Systems

(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations

bull Project will move

data into HPC-

hosted database for

querying and data

product generation

12

bull Goal Understand correlations between automotive performance data

survivability data terrain meteorology and other conditions



Summary

bull TRMC is developing a plan to act upon the Knowledge

Management (KM) recommendations from the Comprehensive

Review of TampE Infrastructure

ndash Recommendation 1 Use DoD cloud solution for TampE data

ndash Recommendation 2 Establish a DoD-wide KM capability for TampE

bull Improved TampE KM will help achieve better acquisition outcomes

and reduce costs

ndash Identify amp Diagnose problems sooner and continuously

ndash Eliminate unnecessary testing

bull TRMC funded proofs of concept will deliver proven capabilities

ndash Enable ldquoBig Datardquo analytics during JSF TampE

ndash Establish improved transfer of knowledge between fielded and next-

generation systems

13



Questions

14



Backup Slides

Not for presentation

15



Concept Definitions

bull Big Data

ndash Big data is a blanket term for any collection of data sets so large amp complex that it becomes

difficult to process using on-hand data management tools or traditional data processing

applications The challenges include capture curating storage search sharing transfer

analysis amp visualization

bull Big Data Analytics Data Discovery

ndash Process of discovering meaningful new correlations patterns amp trends by sifting through large

amounts of data stored in repositories using pattern recognition technologies as well as

statistical amp mathematical techniques

bull Cloud Computing

ndash The practice of using a network of remote servers hosted on a network to store manage amp

process data rather than a local server or personal computer A private cloud is a marketing

term for a cloud computing platform that is implemented within the corporate firewall under the

control of the IT department

bull Data Center

ndash A facility used to house a large group of networked computer servers storage networking amp

telecommunications equipment This equipment is used by organizations for the remote storage

processing or distribution of large amounts of data Data centers generally include redundant or

backup power supplies redundant data communications connections environmental controls

(eg air conditioning fire suppression) amp various security devices

16



Concept Definitions

bull Knowledge Management (KM)

ndash KM is a discipline that promotes an integrated approach to identifying capturing evaluating

retrieving amp sharing all of an enterprisersquos information assets These assets may include

databases documents policies procedures amp previously un-captured expertise amp experience in

individual workers

bull Portal

ndash A portal is a website which brings information from diverse sources together in a uniform way A

well designed portal can increase a KM systemrsquos value exponentially while using a badly

designed portal is an exercise in frustration A portal is the doorway to the content amp content is

the window to our organizational knowledge

bull Virtual Machine (VM)

ndash In computing a VM is an emulation of a particular computer system VMs operate based on the

computer architecture amp functions of a real or hypothetical computer amp their implementations

may involve specialized hardware software or a combination of both

bull Virtualization Technologies

ndash Virtualization enables you to run multiple application amp operating systems on a single computer

making the IT infrastructure simpler amp more efficient while reducing the overall server footprint amp

operating costs This will more efficiently utilize server resources amp increase capabilities Within

a virtual architecture you can deploy pre-configured applications faster increase performance amp

availability

17



Long-term DoD TampE Enterprise Knowledge Management Vision

bull Knowledge should be readily available amp discoverable across an

acquisition programrsquos entire lifecycle

ndash Enables measured improvements data analytics etc to occur throughout system

lifecycle

bull Ideally analysts program managers amp logisticians would have access to

all data associated with an acquisition system

bull KM system would include data from initial conceptual research amp

development work through all phases of TampE to data gathered while

fielded in theater amp operations amp maintenance records for all acquisition

systems

bull Utilizing cloud computing technologies implement a logically

centralized physically distributed knowledge management system

which leverages existing TampE data centers

bull Allows benefits of cloud computing to be realized for data which cannot

be moved to a centralized location for processing

18


TRMC Knowledge Management VisionCSA RampD

OEM Contractor

CSA TampE

CSA Logistics

Discovery Analysis Tools




Logically Centralized

Data Storage

Search Engine

KM Portal

Classification amp Permissions

Data Scientists

Evaluators

PMrsquos

Developers Engineers

Governance amp Policies

(animated slide) 19

DoD Enterprise Data Management for Acquisition

Analysis Tools


DASD(DTampE) Director TRMC

Staff DirectorLt Col Brian Bohenek

USAF

Principal Deputy DTampE

Vacant

(SES)

DASD(DTampE) Director TRMCDr C David Brown

Principal Deputy Director TRMC

Mr Derrick Hinton

(SES)

bull Monitorreview DTampE activities of

major defense acquisition programs

bull Develop Policy and Guidance

bull Assist Program Offices (Chief

Developmental Testers) in TampE

Planning

bull Test amp Evaluation Master Plan

(TEMP) approvaldisapproval

bull Advocacy for Acquisition DTampE

workforce

bull Annual Report to Congress

bull Steward of the DoD test and

evaluation (TampE) infrastructurendash Major Range and Test Facility Base (MRTFB)

bull Services TampE budget certification

bull TampE Infrastructure Investmentsndash TampE Science and Technology (SampT) Program

ndash Central Test and Evaluation Investment

Program (CTEIP)

ndash Electronic Warfare Infrastructure

Improvement Project (EWIIP)

ndash Joint Mission Environment Test Capability

(JMETC) Program

ndash National Cyber Range (NCR)

bull Biannual Strategic Plan to Congress

DTampE TRMC




(DM-DT) Study


Management










project initiated






things



context



value















Test

Resource

Data

Loggers

Operational

Capability

Data

Loggers

Layer Interface(s)

Data Retrieval

Analysis

Presentation

No

n-ldquo

Re

al-

Tim

erdquo D

ata

Tra

ns


Real-Time Post-Test

Processing

Generates TampE

Data

Captures TampE

Data

Where Data

becomes

Knowledge




6

Level 1 Raw Data



Level 4


Level 5


Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ










obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools




(DM-DT) Study


Management










project initiated






things



context



value















Test

Resource

Data

Loggers

Operational

Capability

Data

Loggers

Layer Interface(s)

Data Retrieval

Analysis

Presentation

No

n-ldquo

Re

al-

Tim

erdquo D

ata

Tra

ns


Real-Time Post-Test

Processing

Generates TampE

Data

Captures TampE

Data

Where Data

becomes

Knowledge




6

Level 1 Raw Data



Level 4


Level 5


Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ










obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools




things



context



value















Test

Resource

Data

Loggers

Operational

Capability

Data

Loggers

Layer Interface(s)

Data Retrieval

Analysis

Presentation

No

n-ldquo

Re

al-

Tim

erdquo D

ata

Tra

ns


Real-Time Post-Test

Processing

Generates TampE

Data

Captures TampE

Data

Where Data

becomes

Knowledge




6

Level 1 Raw Data



Level 4


Level 5


Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ










obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools







Test

Resource

Data

Loggers

Operational

Capability

Data

Loggers

Layer Interface(s)

Data Retrieval

Analysis

Presentation

No

n-ldquo

Re

al-

Tim

erdquo D

ata

Tra

ns


Real-Time Post-Test

Processing

Generates TampE

Data

Captures TampE

Data

Where Data

becomes

Knowledge




6

Level 1 Raw Data



Level 4


Level 5


Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ










obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools




6

Level 1 Raw Data



Level 4


Level 5


Level 6

Extended Analysis

Level 7

Conclusion

Test Report

Delivered to PM

Customer

Limited archival

at test facility

Deleted after

analysis complete

Delivered to HQ










obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools









obtain knowledge











User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



User


8








Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools

Savings








w Other Systems



Systems




Test Planning

Test Setup


System Fielding





bull Reduced TDY
















10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools













10





User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



User

Eglin

Pax

River

JSF-KM Test Concept











11

JPO

Pote

ntia

l Expansio

n




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools




(TampE-DAIOFS)

bull 20 TB of Mine

Resistant Ambush

Protected (MRAP)

data collected

during DT OT and

combat operations


data into HPC-

hosted database for

querying and data

product generation

12





Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



Summary







and reduce costs






generation systems

13



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



Questions

14



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



Backup Slides


15



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



Concept Definitions

bull Big Data














bull Data Center






16



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



Concept Definitions





individual workers

bull Portal














availability

17







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools







lifecycle






systems






18



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools



OEM Contractor

CSA TampE

CSA Logistics






Data Storage

Search Engine

KM Portal


Data Scientists

Evaluators

PMrsquos



(animated slide) 19


Analysis Tools

Documents

Reducing Risk through Improved T&E Knowledge Management · value –Example: If the ... that rapidly answer questions and discover “unknown unknowns” ... • By embracing KM &