Data-Ed: Show Me the Money: The Business Value of Data and ROI

TITLE

Welcome!
Monetizing Data Management:
Business Value of Data and ROI

Date: December 11, 2012
Time: 2:00 PM ET
Presenter: Dr. Peter Aiken

PRODUCED BY CLASSIFICATION DATE SLIDE
DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 1
12/07/12 © Copyright this and previous years by Data Blueprint - all rights reserved!

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comments and collaborate with fellow
@paiken
Find industry news, insightful data management
Ask questions and submit
content professionals
your comments: #dataed
and event updates.


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Meet Your Presenter: Dr. Peter Aiken
• Internationally recognized thought-leader in
the data management field with more than 30
years of experience
• Recipient of the 2010 International Stevens
Award
• Founding Director of Data Blueprint
(http://datablueprint.com)
• Associate Professor of Information Systems
at Virginia Commonwealth University
(http://vcu.edu)

• President of DAMA International (http://dama.org)
• DoD Computer Scientist, Reverse Engineering Program Manager/
Office of the Chief Information Officer
• Visiting Scientist, Software Engineering Institute/Carnegie Mellon
University
• 7 books and dozens of articles
• Experienced w/ 500+ data management practices in 20 countries


Monetizing Data
Management:
Business Value
of Data and ROI

Professional Development: Business Value of Data and ROI
DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION

TITLE

Outline
1. Data Management Overview
2. Root Cause Analysis
3. Ineffective Data Management
Investments
4. Success Stories & Monetization
Examples
5. Guiding Principles
6. Take Aways and Q&A

Tweeting now:
#dataed


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The DAMA Guide to the Data Management Body of Knowledge
Published by DAMA
International
• The professional
association for Data
Managers (40
chapters worldwide)
DMBoK organized
around
• Primary data
management
functions focused
around data delivery
to the organization
• Organized around
several
environmental
elements

Data
Management
Functions

TITLE

The DAMA Guide to the Data Management Body of Knowledge

Amazon:
http://
www.amazon.com/
DAMA-Guide-
Management-
Knowledge-DAMA-
DMBOK/dp/
0977140083
Or enter the terms
"dama dm bok" at the
Amazon search
engine

Environmental Elements

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What is the CDMP?
• Certified Data Management
Professional
• DAMA International and ICCP
• Membership in a distinct group made
up of your fellow professionals
• Recognition for your specialized
knowledge in a choice of 17 specialty
areas
• Series of 3 exams
• For more information, please visit:
– http://www.dama.org/i4a/pages/
index.cfm?pageid=3399
– http://iccp.org/certification/
designations/cdmp


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Data Management


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Data Management
Manage data coherently.

Data Program
Coordination
Share data across boundaries.
Organizational
Data Integration

Data Stewardship Data Development

Assign responsibilities for data.
Engineer data delivery systems.

Data Support
Operations

Maintain data availability.


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Outline
Investments
Examples

Tweeting now:
#dataed


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IT Project Failure Rates
Recent IT project failure rates statistics
can be summarized as follows:
– Carr 1994
• 16% of IT Projects completed
on time,
within budget, with full
functionality
– OASIG Study (1995)
• 7 out of 10 IT projects "fail" in
some respect
– The Chaos Report (1995)
• 75% blew their schedules by 30% or more
• 31% of projects will be canceled before they ever get completed
• 53% of projects will cost over 189% of their original estimates
• 16% for projects are completed on-time and on-budget
– KPMG Canada Survey (1997)
• 61% of IT projects were deemed to have failed
– Conference Board Survey (2001)
• Only 1 in 3 large IT project customers were very “satisfied”

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More IT Project Failure Rates
Recent IT project failure rates statistics
can be summarized as follows:
– Robbins-Gioia Survey (2001)
• 51% of respondents viewed
their large IT implementation
project as unsuccessful
– MacDonalds Innovate (2002)
• Automate fast food network
from fry temperature to # of
burgers sold-$180M USD
write-off
– Ford Everest (2004)
• Replacing internal purchasing
systems-$200 million over
budget
– FBI (2005)
• Blew $170M USD on
suspected terrorist
database-"start over from
scratch"
http://www.it-cortex.com/stat_failure_rate.htm; (accessed 9/14/02); New York Times 1/22/05

60% IT Project Failure Rates (moving average)

53% 53%
51%
49%
45% 46%
44%

40%

34%
33%
30% 31%
32%

29%
28% 28%
27%
26%
24%
23%

18%
15% 16%
15%

Failed Challenged Succeeded

0%
1994 Click 1993 Master text styles 2000
to edit 1998 2002 2004 2009
Source: Standish Chaos Reports as reported at: http://www.galorath.com/wp/software-project-failure-costs-billions-better-estimation-planning-can-help.php

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% of DM Organizations labeled “successful”
0.45

0

Successful Partial Success Don't know/too soon to tell Unsuccessful Does not exist
1981 2007


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DM Origins – Which arrives first: DM or DBMS?

• A key indicator of organizational awareness
• 75% reacting instead of anticipating
• Best practices are obvious

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Data Management Involvement


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Expanding DM Scope


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$0 $125,000 $250,000 $375,000 $500,000

• Assessed 1200
migration projects!
Median Project Expense
– Surveyed only
experienced migration
specialists who have
done at least four
migration projects
Median Project Cost
• The median project
costs over 10 times the amount planned!
• Biggest Challenges: Bad Data; Missing Data; Duplicate Data
• The survey did not consider projects that were cancelled largely
due to data migration difficulties
• "… problems are encountered rather than discovered"
Joseph R. Hudicka "Why ETL and Data Migration Projects Fail" Oracle Developers Technical Users Group Journal June 2005 pp. 29-31


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Organizations Surveyed
• Results from
more than 500
International Organizations organizations
10%Local Government
4% • 32% government
State Government Agencies • Appropriate
17%
public company
representation
• Enough data to
Federal Government demonstrate
11% European
organization DM
Public Companies
practices are
58% generally more
mature

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Polling Question #1
What percentage of Data Management investments
achieve tangible returns?

a. 30%
b. 10%
c. 65%


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Largely Ineffective EIM Investments
• Approximately, 10%
percent of organizations
achieve parity and
Investment <= Return
(potential positive 10%
returns) on their DM
investments.
• Only 30% of DM
investments achieve Return ≈ 0
tangible returns at all. 70% Investment > Return
20%
• Seventy percent of
organizations have very
small or no tangible
return on their DM
investments.

TITLE

Outline
Investments
Examples

Tweeting now:
#dataed


Root Cause Analysis
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• Symptom of the
problem
– The weed
– Above the surface
– Obvious
• The underlying Cause
– The root
– Below the surface
– Not obvious
• Poor Information
Management
Practices


Ishikawa Fishbone Diagrams
TITLE

• Why is infant mortality so high? • Why are so many organizational technology
– Malnourished mothers experiences so poor?
• Why are mothers malnourished? – Misunderstanding of data's role in IT
– Substandard biology educations in high school • Why do so few understand data's role in IT?
• Why do are biology programs substandard? – Little, if any, focus on enterprise-wide data
– Poor education of high school biology teachers
use in the educational system
• Why do we have poor biology teacher education?
– Biology profession unaware of consequences • Why is the educational system not
addressing this gap?
– Lack of recognition by the system
• Why has the system not yet been made
aware of this deficiency?
– Lack of understanding at the C-level of
these issues
• Why do they not understand?
– Little, if any, focus on enterprise-wide data
use in the educational system

Asking "why"
repeatedly!

TITLE

Toyota versus Detroit Engine Mounting
Detroit
• 3 different bolts
• 3 different
wrenches
• 3 different bolt
inventories

Toyota
• Same bolts used
for all three
assemblies
• 1 bolt inventory
• 1 type of wrench


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Academic Research Findings
0% 12.500% 25.000% 37.500% 50.000%

Retail
49.00%
Consulting
39.00%
Air Transportation
21.00%

Food Products
20.00%

Construction
20.00%
Steel A 10% improvement in
20.00%
Automobile data usability on
Publishing
19.00% productivity
18.00%
(increased sales per
Industrial Instruments
employee by 14.4% or
Telecommunications 18.00%
$55,900)
17.00%
DATA BLUEPRINTImpacts of Effective Data by Anitesh Barua,, Deepa Mani,, Rajiv Mukherjee
Measuring the Business 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 27

TITLE

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Projected impact of a 10%
improvement in data quality and
sales mobility on Return on Equity

PRODUCED BY Impacts of Effective Data by Anitesh Barua,, Deepa Mani,, Rajiv Mukherjee
Measuring the Business
PRODUCED BY CLASSIFICATION DATE
CLASSIFICATION* DATE SLIDE
SLIDE
DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060
EDUCATION 28
30
12/07/12
12/7/12 © Copyright this and previous years byby Data Blueprint allall rights reserved!
© Copyright this and previous years Data Blueprint - - rights reserved!

TITLE
TITLE

Projected Impact of a 10% increase
in intelligence and accessibility of
data on Return on Assets

Measuring the Business Impacts of Effective Data by Anitesh Barua,, Deepa Mani,, Rajiv Mukherjee
PRODUCED BY CLASSIFICATION* DATE SLIDE
EDUCATION 29
31
12/07/12
© Copyright this and previous years by Data Blueprint - all rights reserved!

TITLE

Outline
Investments
Examples

Tweeting now:
#dataed


TITLE
TITLE Monitization: Time & Leave Tracking

At Least 300 employees are
spending 15 minutes/week
tracking leave/time

PRODUCED BY CLASSIFICATION* DATE SLIDE
DATA BLUEPRINT 10124-CDataW. BROAD reserved!
DATA BLUEPRINT 10124-C BROAD ST, GLEN ALLEN, VA 23060
W.Blueprint - all rights ST, GLEN ALLEN, VA 23060 EDUCATION
EDUCATION 32
12/7/12 © Copyright this and previous years by
31

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Capture Cost of Labor/Category

- datablueprint.com
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33

Computer Labor as Overhead
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Routine Data Entry
District-L (as an example) Leave Tracking Time Accounting
Employees 73 50
Number of documents 1000 2040
Timesheet/employee 13.70 40.8
Time spent 0.08 0.25
Hourly Cost $6.92 $6.92
Additive Rate $11.23 $11.23
Semi-monthly cost per $12.31 $114.56
timekeeper
Total semi-monthly $898.49 $5,727.89
timekeeper cost
Annual cost $21,563.83 $137,469.40

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Annual Organizational Totals
• Range $192,000 - $159,000/month
• $100,000 Salem
• $159,000 Lynchburg
• $100,000 Richmond
• $100,000 Suffolk
• $150,000 Fredericksburg
• $100,000 Staunton
• $100,000 NOVA
• $800,000/month or $9,600,000/annually
• Awareness of the cost of things considered overhead


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ERP Implementation Success
On time, within budget, as planned 10%
350%

300%

250%

200%
230%
Overrun 55% 178%
Cancelled 35% 150%

100%

59%
50%
100% 100%
41%
0%

Cost Schedule Planned
Functionality
• Most ERP implementations today result in cost and
schedule overruns; courtesy of the Standish Group

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Predicting Engineering Problem Characteristics

Platform: Amdahl
OS: MVS Platform: UniSys
1998 Age: 15 OS: OS
Data Structure: VSAM/virtual 1998 Age: 21
Legacy System Legacy System
database tables Data Structure: DMS (Network)
#1: Payroll #2: Personnel
Physical Records: 780,000 Physical Records: 4,950,000
Logical Records: 60,000 Logical Records: 250,000
Relationships: 64 Relationships: 62
Entities: 4/350 Entities: 57
Attributes: 683 Attributes: 1478

Characteristics Logical Physical
Platform: WinTel Records: 250,000 600,000
OS: Win'95 Relationships: 1,034 1,020
1998 Age: new Entities: 1,600 2,706
Data Structure: Client/Sever RDBMS Attributes: 15,000 7,073

New System


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"Extreme" Data Engineering
• 2 person months = 40 person days
• 2,000 attributes mapped onto 15,000
• 2,000/40 person days = 50 attributes
per person day
or 50 attributes/8 hour = 6.25 attributes/hour
and
• 15,000/40 person days = 375 attributes
per person day
or 375 attributes/8 hours = 46.875
attributes/hour
• Locate, identify, understand, map, transform,
document, QA at a rate of -
• 52 attributes every 60 minutes or
.86 attributes/minute! CLASSIFICATION DATE SLIDE
PRODUCED BY

TITLE


TITLE

Reverse Engineering PeopleSoft
implementation Component
representation metadata integration Metadata Uses

• System Structure
• Queries to Installed Metadata -
PeopleSoft
PeopleSoft System requirements
Internals workflow metadata verification and
system change
TheMAT analysis

• PeopleSoft system structure metadata • Data Metadata - data
external post conversion, data
RDBM derivation security, and user
metadata training
Tables analysis
and
integration • Workflow Metadata -
• Printed business practice
PeopleSoft analysis and
Datamodel realignment
data metadata

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PeopleSoft Process Metadata

Home Page Name Home Page

(relates to one or more)

Business Process
Business Process Name Name

Business Process
Business Process Component Name Component

Business Process
Component Step
Business Process Component Step Name


TITLE

Example Query Outputs

- datablueprint.com
12/07/12 © Copyright this and previous years by Data Blueprint - all rights reserved! 1/4/2011 © Copyright this and previous years by Data Blueprint - all rights reserved!
42

TITLE


Resolution
TITLE

Quantity System Time to Labor Hours
Component make
change
1,400 Panels 15 minutes 350
1,500 Tables 15 minutes 375
984 Business 15 minutes 246
process
component
steps
Total 971
X $200/hour $194,200
X 5 upgrades $1,000,000

TITLE
Improving Data Quality during System Migration

• Challenge
– Millions of NSN/SKUs
maintained in a catalog
– Key and other data stored in
clear text/comment fields
– Original suggestion was
manual approach to text extraction
– Left the data structuring problem unsolved
• Solution
– Proprietary, improvable text extraction process
– Converted non-tabular data into tabular data
– Saved a minimum of $5 million
– Literally person centuries of work

TITLE Determining Diminishing Returns
Unmatched Ignorable Items
Items Items Matched
Week # (% Total) (% Total) (% Total)
1 31.47% 1.34% N/A
2 21.22% 6.97% N/A
3 20.66% 7.49% N/A
4 32.48% 11.99% 55.53%
… … … …
14 9.02% 22.62% 68.36%
15 9.06% 22.62% 68.33%
16 9.53% 22.62% 67.85%
17 9.50% 22.62% 67.88%
PRODUCED BY
18 7.46%
22.62% 69.92%
CLASSIFICATION DATE
EDUCATION
SLIDE
45

Quantitative Benefits
TITLE

Time needed to review all NSNs once over the life of the project:
NSNs 2,000,000
Average time to review & cleanse (in minutes) 5
Total Time (in minutes) 10,000,000

Time available per resource over a one year period of time:
Work weeks in a year 48
Work days in a week 5
Work hours in a day 7.5
Work minutes in a day 450
Total Work minutes/year 108,000

Person years required to cleanse each NSN once prior to migration:
Minutes needed 10,000,000
Minutes available person/year 108,000
Total Person-Years 92.6

Resource Cost to cleanse NSN's prior to migration:
Avg Salary for SME year (not including overhead) $60,000.00
Projected Years Required to Cleanse/Total DLA Person Year 93
Saved
Total Cost to Cleanse/Total DLA Savings to Cleanse NSN's: CLASSIFICATION DATE $5.5SLIDE
million
PRODUCED BY

TITLE


Seven Sisters from British Telecom
TITLE

Thanks to Dave Evans


TITLE
Date: Tue, 26 Mar 2002 10:47:52 -0500
From: Jamie McCarthy <jamie@mccarthy.vg>
Subject: Friendly Fire deaths traced to dead battery

In one of the more horrifying incidents I've read about, U.S. soldiers and
allies were killed in December 2001 because of a stunningly poor design of a
GPS receiver, plus "human error."

http://www.washingtonpost.com/wp-dyn/articles/A8853-2002Mar23.html

A U.S. Special Forces air controller was calling in GPS positioning from
some sort of battery-powered device. He "had used the GPS receiver to
calculate the latitude and longitude of the Taliban position in minutes and
seconds for an airstrike by a Navy F/A-18."
Friendly
Fire deaths
According to the *Post* story, the bomber crew "required" a "second
calculation in 'degree decimals'" -- why the crew did not have equipment to
perform the minutes-seconds conversion themselves is not explained.

The air controller had recorded the correct value in the GPS receiver when
traced to
Dead
the battery died. Upon replacing the battery, he called in the
degree-decimal position the unit was showing -- without realizing that the
unit is set up to reset to its *own* position when the battery is replaced.

The 2,000-pound bomb landed on his position, killing three Special Forces
Battery
soldiers and injuring 20 others.

If the information in this story is accurate, the RISKS involve replacing
memory settings with an apparently-valid default value instead of blinking 0
or some other obviously-wrong display; not having a backup battery to hold
values in memory during battery replacement; not equipping users to
translate one coordinate system to another (reminiscent of the Mars Climate
Orbiter slamming into the planet when ground crews confused English with
metric); and using a device with such flaws in a combat situation

SLIDE
PRODUCED BY
DATACopyright this and previous years by DataW. BROAD reserved!
BLUEPRINT 10124-C Blueprint - all rights ST, GLEN ALLEN, VA 23060 EDUCATION
EDUCATION 50
12/07/12 ©

TITLE

Messy Sequencing Towards Arbitration
Plaintiff Defendant
(Company X) (Company Y)

April Requests a Responds indicating
recommendation from "Preferred Specialist"
ERP Vendor status
July Contracts Defendant to Begins
implement ERP and implementation
convert legacy data
January Realizes a key milestone Stammers an
has been missed explanation of "bad"
data
July Slows then stops Removes project team
Defendant invoice
payments
Files arbitration request
as governed by contract
with Defendant

TITLE

Expert Reports
Expert Report
Ours provided evidence that :
1. Company Y's conversion code introduced
errors into the data
2. Some data that Company Y converted was of
measurably lower quality than the quality of the data
before the conversion
3. Company Y caused harm by not performing an analysis
of the Company X's legacy systems and that that the
required analysis was not a part of any project plan used
by Company Y
4. Company Y caused harm by withholding specific
information relating to the perception of the on-site
consultants' views on potential project success


TITLE
TITLE
AJHR0213_CAN_UPDATE.SQR
!************************************************************************
! Procedure Name: 230-Assign-PS-Emplid
!
! Description : This procedure generates a PeopleSoft Employee ID
! (Emplid) by incrementing the last Emplid processed by 1 The defendant knew to
! First it checks if the applicant/employee exists on
! the PeopleSoft database using the SSN. prevent duplicate SSNs
!
!************************************************************************
Begin-Procedure 230-Assign-PS-Emplid

The exclamation point
move 'N' to $found_in_PS !DAR 01/14/04
move 'N' to $found_on_XXX !DAR 01/14/04 prevents this line from
BEGIN-SELECT -Db'DSN=HR83PRD;UID=PS_DEV;PWD=psdevelopment'
looking for duplicates, so
NID.EMPLID no check is made for a
NID.NATIONAL_ID
duplicate SSN/National
move 'Y' to $found_in_PS
move &NID.EMPLID to $ps_emplid
!DAR 01/14/04
ID
FROM PS_PERS_NID NID
!WHERE NID.NATIONAL_ID = $ps_ssn
WHERE NID.AJ_APPL_ID = $applicant_id
END-SELECT
Legacy systems business
rules allowed employees to
if $found_in_PS = 'N' !DAR 01/14/04
do 231-Check-XXX-for-Empl !DAR 01/14/04 have more than one
if $found_on_XXX = 'N'
add 1 to #last_emplid
!DAR 01/14/04
AJ_APPL_ID.
let $last_emplid = to_char(#last_emplid)
let $last_emplid = lpad($last_emplid,6,'0')
let $ps_emplid = 'AJ' || $last_emplid
end-if
end-if !DAR 01/14/04

72
End-Procedure 230-Assign-PS-Emplid
SLIDE
PRODUCED BY
EDUCATION 53

TITLE


TITLE
Risk Response
“Risk response development involves defining enhancement steps
for opportunities and threats.”
Page 119, Duncan, W., A Guide to the Project Management Body of Knowledge, PMI, 1996

Tasks Hours "The go-live date may need to
New Year Conversion 120
Tax and payroll balance conversion 120
be extended due to certain
General Ledger conversion 80 critical path deliverables not
Total 320 being met. This extension will
require additional tasks and
Resource Hours
G/L Consultant 40
resources. The decision of
Project Manager 40 whether or not to extend the
Recievables Consultant 40 go-live date should be made
HRMS Technical Consultant 40 by Monday, November 3,
Technical Lead Consultant 40 20XX so that resources can
HRMS Consultant 40
Financials Technical Consultant 40
be allocated to the additional
Total 280 tasks."
Delay Weekly Resources Weeks Tasks Cumulative
January (5 weeks) 280 5 320 1720
February (4 weeks) 280 4 1120
Total 2840

TITLE

Outline
Investments
Examples

Tweeting now:
#dataed


TITLE

The Defense's "Industry Standards"
• Question:
– What are the industry standards that you are referring to?
• Answer:
– There is nothing written or codified, but it is the standards which
are recognized by the consulting firms in our (industry).
• Question:
– I understand from what you told me just a moment ago that the
industry standards that you are referring to here are not written
down anywhere; is that correct?
• Answer:
– That is my understanding.
• Question:
– Have you made an effort to locate these industry standards and
have simply not been able to do so?
• Answer:
– I would not know where to begin to look.


TITLE

Published Industry Standards Guidance
Examples from the:
• IEEE (365,000 members)
– Institute of Electrical and Electronic Engineers
– 150 countries, 40 percent outside the United States
– 128 transactions, journals and magazines
– 300 conferences
• ACM (80,000+ members)
– Association of Computing Machinery
– 100 conferences annually
• ICCP (50,000+ members)
– Institute for Certification of Computing Professionals
• DAMA International (3,500+ members)
– Data Management Association
– Largest Data/Metadata conference

TITLE


TITLE
ACM Code of Ethics and Professional Conduct

1. General Moral Imperatives.
1.2 Avoid harm to others
• Well-intended actions, including those that accomplish assigned
duties, may lead to harm unexpectedly. In such an event the
responsible person or persons are obligated to undo or mitigate
the negative consequences as much as possible. One way to
avoid unintentional harms is to carefully consider potential
impacts on all those affected by decisions made during
design and implementation.
• To minimize the possibility of indirectly harming others,
computing professionals must minimize malfunctions by
following generally accepted standards for system design and
testing. Furthermore, it is often necessary to assess the social
consequences of systems to project the likelihood of any serious
harm to others. If system features are misrepresented to users,
coworkers, or supervisors, the individual computing professional is
responsible for any resulting injury.


TITLE

Outcome

Jan 4, 2011


TITLE

Polling Question #2
Which is not a reason why data scientist add
business value?

a. Act as a data-to-business translator
b. They work side-by-side with the IT department
c. Conduct problem solving using a data-driven
approach


TITLE
3 Ways Data Scientists Add Business Value
1. Refine target audiences. The more information that companies gather and
analyze about their customers, the more they learn about their behaviors,
needs, and preferences. This information also provides greater knowledge
about the lifecycle stage that a particular set of customers is at (e.g. dual-
income with children nearing college age). This type of information can help
companies identify the most likely customers for certain products and
services. Data analysts are masters at distilling this type of information.
2. Conduct problem solving using a quantifiable, data-driven approach. For
years, executives have made million-dollar decisions based on gut instinct.
But that’s no longer necessary with the volume of data that’s available from so
many channels and market sources for decision makers to pore over. Not only
can data analysts help senior leaders make the right decisions based on facts,
they can also provide impartial, data-led guidance for critical decisions when
the top brass are deadlocked on the right path to take.
3. Acting as a data-to-business translator. Many companies struggle with
communicating and interpreting the results from analytics efforts. Data
analysts can fill a critical role here by helping senior executives make sense of
the data that’s being presented to them as well as by helping them understand
how the information can be applied to various areas of the business.


TITLE

Outline
Investments
Examples

Tweeting now:
#dataed


TITLE
Data Management: Why is it Important to Your Organization?
• Why is it important?
– Concretizing
• State Agency Time & Leave Tracking
– $10 million USD annually
• ERP Implementation
$1 million USD on a large project
• Data Warehouse Quality Analysis
$5 billion USD US DoD (prevention)
• MDM British Telecom rollout
– £ 250 (small investment)
• Non-Monetized Example
– Different measures
• ERP Implementation Legal Case
$ 5,355,450 CAN damages/penalties

TITLE

Questions?

+ =

It’s your turn!
Use the chat feature or Twitter (#dataed) to submit
your questions to Peter now.


TITLE

Upcoming Events
January Webinar: Unlocking Business Value through Data Modeling
and Data Architecture (Part I of II)
2013 @ 2:00 PM – 3:30 PM ET
(11:00 AM-12:30 PM PT)

February: Unlocking Business Value
through Data Modeling
and Data Architecture
(Part II of II)
2013 @ 2:00 PM – 3:30 PM ET
(11:00 AM-12:30 PM PT)

Sign up here:
• www.datablueprint.com/webinar-schedule
• www.Dataversity.net
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