Creating a Big Data Strategy with Tactics for Quick Implementation

Gregory Lewandowski

@lewandog

Gregory Lewandowski (@lewandog)Chief Solutions Officer at Icimo (Data Kingpin)

Icimo• Customers, Staff

• Training

• CoE’s (Center of Excellence)

• Enterprise

Data Leadership

Icimo helps organizations become data driven through a combination of software and services enabling data

discovery, visualization, and analysis.

“When you empower users to answer their own questions,

you transform the user-data relationship.”

“Data is the new oil. Data is just

like crude. It’s valuable, but if

unrefined it cannot really be used”

~ Clive Humby

New “Refining” Companies

Big Data

Big Data Facts

• Every 2 days, we create as much data as the world did from the beginning of creation through 2003.

• The amount of data transferred over mobile networks increases by (guess) per month.

• By 2020, we will have over 10 Billion Mobile Smart Devices will be in use.

• Trillions of sensors will be in place by the year 2020 to monitor, track and communicate.

• For a typical Fortune 1000 company, just a 10% increase in data accessibility will result in more than $65 million additional net income.

• At the moment less than (guess) of all data is ever analyzed and used, just imagine the potential here.

3V’s of Big Data(Gartner - Doug Laney, 2001)

Volume Amount of Data

Variety Range of Data Types

Velocity Speed of Data In/Out

Big Data Reality

Call it big data if you:

• Run out of memory

• Run out of storage

• Run out of time

• Have challenges moving it

…And

Require new skills, technologies or processing to aid in unlocking the value in the data.

Speaker Name OverallAverage Practical_KnowledgeAverage ReleventAverage BarriersAverage DifficultyAverage #Sessions

Sample Speaker 4.43 4.35 4.37 4.12 3.32 6

Sample Speaker 4.70 4.64 4.51 4.42 3.35 2

Sample Speaker 4.57 4.43 4.50 4.31 3.32 2

Sample Speaker 4.29 4.15 4.26 3.89 3.40 2

Sample Speaker 4.10 4.15 4.26 3.89 3.40 2

Sample Speaker 4.11 4.15 4.26 3.89 3.40 2

Sample Speaker 4.47 4.34 4.48 4.11 3.33 4

Sample Speaker 4.54 4.46 4.47 4.24 3.49 4

Sample Speaker 4.20 3.99 4.19 3.82 3.34 2

Sample Speaker 4.81 4.76 4.73 4.53 3.41 8

Sample Speaker 4.54 4.46 4.36 4.20 3.34 2

Sample Speaker 4.62 4.45 4.58 4.32 3.70 1

Sample Speaker 4.41 4.23 4.35 4.15 3.33 2

Sample Speaker 4.62 4.39 4.21 4.31 3.28 5

Big Data Reality

2009 - Hyatt Regency Washington, DCWed Thurs Fri Sat Sun Mon Tue Mon Tues Wed

Total P/U %Date 8-Jul 9-Jul 10-Jul 11-Jul 12-Jul 13-Jul 14-Jul 15-Jul

Block 0 0 0 0 40 50 40 13092%

P/U 1 1 4 12 30 48 22 1 119

Attrition Set At: 80%

Attrition Fee's paid: $0

Room Rate: $xxx

Room Revenue $xx,xxx

F/B (excluding T/G)

F/B (including T/G) $xx,xxx

Number of Attendees: 115

Comments:

Month Division v0 Campaigns v0 Tactic Type v0 Tactic v0

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Offline Fax

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Offline Direct mail

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Comp Review Prep 2012 Online Email

March 2012Continuing Education Review Express 2012 Email

March 2012Continuing Education Comp Review Prep 2012 Offline Direct mail

March 2012Continuing Education Review Express 2011 P&S

March 2012Continuing Education 2012 CME Portfolio Email

March 2012Continuing Education 2012 CME Portfolio Email

Creating Success

SpeedCommunication

Our World Has Changed

1983 – The World Changed

1983 - The World Changed

• Net new category of tools which made it easier for those who know the data to work with it…

• Validation / catalyst of the personal computer

• Led to Excel, the most widely used BI tool in the world

• Forced changes in roles, processes and people

• Characteristics

• Simple

• Fast

• Less coding

Today - The World Changed (Again)

• Net new category of tools which makes it easier for those who know the data to work with it…

• Forced changes in roles, processes and people

• Disrupting traditional BI

• Characteristics

• Simple

• Fast

• Less codingmore canvas

• Instant feedback

New Category of BI Tools

• Tableau

• Qlik

• Spotfire

• MS Power BI

• Knime

• RapidMiner

• Alteryx

Opinion-Based Data-Driven

Experience

People

Time

Want

Can

8%

Speed to Opinion(Weeks/Months)

Conventional Self-Reliant

Speed to Insight(Seconds/Minutes)

Want Can

80%

Report Factory

App

Take Advantage of the New Tools

If you don’t, somebody else will…

Data discovery tools have crushed the top-down camp’s monopoly of BI.

~ Wayne Eckerson

Getting Your Point Across

The Concept is Simple

So Why This?2012 2011 2010

Weeks

Out

Report

Date

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20 06/01/12 687 24 622 1,333 16% 504 16 578 1,098 597 12 551 1,160

19 06/08/12 762 30 681 1,473 18% 526 18 595 1,139 651 14 592 1,257

18 06/15/12 846 32 738 1,616 19% 575 22 643 1,240 709 18 621 1,348

17 06/22/12 938 34 798 1,770 22% 676 23 759 1,458 782 20 683 1,485

16 06/29/12 1,052 34 857 1,943 24% 740 28 825 1,593 857 26 735 1,618

15 07/06/12 1,154 35 912 2,101 27% 800 30 885 1,715 970 30 811 1,811

14 07/13/12 1,243 37 981 2,261 29% 879 35 952 1,866 1,048 35 850 1,933

13 07/20/12 1,433 45 1,068 2,546 33% 976 38 1,044 2,058 1,169 44 913 2,126

12 07/27/12 1,698 48 1,227 2,973 39% 1,102 46 1,143 2,291 1,305 47 987 2,339

11 08/03/12 2,007 50 1,450 3,507 46% 1,247 52 1,251 2,550 1,449 48 1,075 2,572

10 08/10/12 2,196 54 1,600 3,850 51% 1,409 63 1,431 2,903 1,722 51 1,205 2,978

9 08/17/12 2,415 70 1,735 4,220 56% 1,725 75 1,692 3,492 2,010 63 1,360 3,433

8 08/24/12 2,650 78 1,862 4,590 61% 2,066 86 1,965 4,117 2,253 72 1,508 3,833

7 08/31/12 2,911 85 1,991 4,987 67% 2,331 94 2,143 4,568 2,502 79 1,670 4,251

6 09/07/12 3,292 105 2,297 5,694 76% 2,719 113 2,588 5,420 2,855 91 2,033 4,979

5 09/14/12 4,053 160 2,811 7,024 93% 3,583 155 3,249 6,987 3,675 136 2,443 6,254

Instead of This?

Why This…?

Instead of This…?

StorytellingStory (noun) is defined as _“An account of imaginary or real people and events told for entertainment.”

Important

Detail

CharacterPlotConflictClimaxPerspective

Stories

Keys to Success

• Move Fast

• Use the tools which will get you tangible results quickly

• Reward ingenuity

• Deliver Visual Analysis, Not Just Reports

• Get some training

• Make your work useful

• Make it personal / customized

• Empower your audience

• Don’t swing for the fences every time

“If the rate of change on the

outside exceeds the rate of

change on the inside, the end is

near.”

~ Jack Welch

Enjoy the

Ride!!

Data+Women

• Identify and talk about issues unique to women in the data industry.

• Meet regularly to foster frank discussion on topics that are otherwise hard to broach.

• Build a community that empowers women in the data industry• Rally around initiatives for further education, training, and

partnership, perhaps even impacting the greater good for women using their analytical talents.

LinkedIn:

data+women+triangle

Anna Kirkland Smith

Contact Me

(@lewandog)