Drive It Home: A Roadmap for Today's Data-Driven Culture

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Grab some coee and enjoy the pre-show banter before the top of the hour!

Transcript of Drive It Home: A Roadmap for Today's Data-Driven Culture

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Grab some

coffee and

enjoy the

pre-show

banter before

the top of the

hour!

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The Briefing Room

Drive It Home: A Roadmap for Today's Data-Driven Culture

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Welcome

Host: Eric Kavanagh

[email protected] @eric_kavanagh

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  Reveal the essential characteristics of enterprise software, good and bad

  Provide a forum for detailed analysis of today’s innovative technologies

 Give vendors a chance to explain their product to savvy analysts

  Allow audience members to pose serious questions... and get answers!

Mission

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Topics

February: DATA IN MOTION

March: BI/ANALYTICS

April: BIG DATA

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Parmenides and the Truth of Now

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Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected] @robinbloor

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Tableau

  Tableau builds software for data visualization, business intelligence and analytics

  Its products include Tableau Desktop, Tableau Public, Tableau Online and Tableau Drive

  Tableau Drive is a methodology designed to create an analytic culture throughout an organization

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Guest: Ted Wasserman

Ted Wasserman is Senior Product Manager at Tableau Software. Ted leads Tableau's data strategy and execution. This includes product planning, setting the strategic vision, and leading the execution of new features and integration with technology vendors. Prior to joining Tableau, Ted worked at IBM for seven years in the Information Management division in a number of different roles including technical consulting, channel marketing, and business development. Ted holds a bachelor's degree and master's degree in computer science from Queen's University.

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A practical roadmap for ���scaling your analytic culture

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The benefits of self-service analytics ���are clear

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Business IT

Requirements Planning Development Test UserExperience Production Analytics

The traditional model fails business users and IT

Users must wait… and are rarely satisfied.

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The Agile model improves waterfall

Production Development

Planning

UserAcceptance Test

Subject MatterExpertise

(requirements)

Keeping business ���closer to development improves quality, ���speed and flexibility.

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��� How do you provide the programmatic

support needed to scale self-service analytics?

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What is Drive?

Tableau Drive is a business intelligence deployment methodology that draws from agile methods and is informed by the most analytically-minded companies in the world. With Tableau Drive, business and IT jointly own the analytics platform. And there is the opportunity to continuously evolve and grow, even at the scale of an enterprise deployment.

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IT Role•  Security•  Data architecture•  Scalability•  Training•  Center of Operations•  Enablement intranet

A partnership that works

Business Role•  Creative analytic work•  Driving data acquisition•  Sharing expertise•  Seeking help when needed•  Evangelism•  Catalyzing action

Execution Enablement

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Discovery Prototyping Foundationbuilding

Scaling out

Drive is a new approach ���to deployment

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Foundationbuilding

Foundation: organizational

•  Center of Operations•  Center of Evangelism•  Executive sponsorship•  Project plan•  Training •  New user onboarding process•  Evangelism activities

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Foundationbuilding

Foundation: technical

•  Sandbox and production environments•  Governance & security policies•  Data dictionary •  Clean, managed & published data sources•  Processes: promotion, escalation, licensing•  Online help desk

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Blueprint for an IT-business partnership

Useful analyticsright away

Proven deploymentstrategies

Broad &sustainableadoption

Key benefits of Drive

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The road forward

Visit our web site for more informationwww.tableau.com/drive

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Perceptions & Questions

Analyst: Robin Bloor

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To Be Agile

Robin Bloor, PhD

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Time To Value

Throughout every generation of IT,

time-to-value has been a priority

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The Old Waterfall

u  Feasibility u  Requirements u  Design u  Development u  Testing u  User testing u  Production u  Review

In the beginning it was the only method for organizing projects.

And there were problems…

Requirements

Feasibility

Design

Development

Testing

UserTesting

Deployment

Review

Cost MultipleFor Correcting

Errors

2-3

2-3

2-3

2-3

2-3

2-3

CumulativeMultiple

4-9

2-3

8-27

16-81

32-243

64-729

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A Fundamental Error

u  The engineering project flow…

u  IT never included the prototyping stage

u  This was never realized until the early 1990s when RAD tools emerged

u  It includes a feedback loop

u  This was the birth of the “Agile Development” movement

2-3

4-9 or 2-3

Planning &Requirements

Design

Prototyping

Deployment

IntegrationTesting

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The Fundamental Mismatch

§  Knows the technology capabilities

§  Has poor knowledge of the real business process

§  Does not know for sure what the business process will become

§  Knows the business process

§  Has poor knowledge of the technology capabilities

§  Does not know for sure what the business process will become

The Developer The End User

This mismatch will never be truly resolved until the developer and the end-user are the same person

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For BI/Analytics…

u  The major difference: The development tools are business oriented

u  Instead of design we have exploration & discovery

u  Prototyping and iteration are still key

u  Deployment may require technicians

u  This has a right to claim agility

BusinessProcessDesign

Exploration& Discovery

Prototyping

Deployment

IntegrationTesting

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The Self Service Trend

The self-service trend in Analytics and BI is an effort to resolve the

fundamental mismatch

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u  How often do you encounter “old methodologies?” How often are they a barrier to progress?

u  Drive seems to require executive sponsorship. Does that mean you have to sell directly to executives?

u  How onerous is the technical side of Foundation?

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u  How much help do businesses/IT need to build and deploy Foundation?

u  Are we short of skilled staff for BI and Analytics (clearly, the evidence suggests we are currently short of data scientists…)?

u  Do we want business analysts to become ersatz data scientists?

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Upcoming Topics

www.insideanalysis.com

February: DATA IN MOTION

March: BI/ANALYTICS

April: BIG DATA

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THANK YOU for your

ATTENTION!

Some images provided courtesy of Wikimedia Commons and Wikipedia