Making Advanced Analytics Simpler:

Challenges, Opportunities, and Value

Fern Halper

TDWI Director of Research, Advanced Analytics

July 23, 2015

@fhalper

Sponsor

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Speakers

John K. Thompson General Manager,

Advanced Analytics, Dell

Fern Halper Research Director,

Advanced Analytics

TDWI

Advanced Analytics

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Advanced analytics provides

algorithms for complex analysis of

either structured or unstructured data.

CHANGE

EXPECTATIONS

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Agenda

Changing expectations

Skills needed

Common pitfalls

Best practices for getting started

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Changing expectations

New platforms

New Users

More users Ease of use

New data

Changing landscape for analytics

More and disparate data

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(source: TDWI 2014)

More advanced

analytics

techniques used

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(source: TDWI 2014)

More platforms

tools and

techniques

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(source: TDWI 2014)

Predictive analytics process

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Problem Identification

Framing problem Identifying data elements

Data Access

Platforms

Data preparation

Cleansing Transformation

Exploration

Model building

Exploration Collaboration

Validation

Model deployment Sharing Scoring

Operationalizing

Model Management

Evaluation/Monitoring Actual Management

**

**

**

New Users are Emerging

Statistician/Modeler Moving towards critical

thinker with

knowledge of the

business- e.g. a

business analyst

More users too

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(source: TDWI 2014)

Democratizing BI

To extend the deployment of BI and analytics

tools to more users in the organization

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Democratization

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0% 5% 10% 15% 20% 25% 30%

70-100%

50-70%

30-50%

10-30%

Consumability

Able to be used

More accessible results

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Advanced Analytics Consumability Trends

Ease of Use

UI, Automation

PA as part of BI package

Collaboration

Platforms

Operationalizing

Model scoring

Embedding

Real time

Platforms

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Another way to look at it

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2. Utilizing Results

1. Model Building

Is this a good thing?

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Skills Needed (1)

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Framing the problem

2. Data Sense

3. Domain

Expertise

1. Critical Thinking

1. Critical Thinking

Ability to formulate a question

Comfortable creatively thinking in numbers and attributes

Interpretation skills

Inference

Above all: Questioning

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2. Domain Expertise

Helps in:

formulating good questions

understanding objectives

assessing the model and taking action on it

Understanding relevant data

Dealing with data outliers, missing data, etc.

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3. Understanding data

Target vs. explanatory variables

Derived variables

Lots of new data types

Documents, graph, location

May require parsing, geocoding

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Skills Needed (2)

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Explain/Defend

6. Storytelling

5. Techniques

4. Tools

4. Understanding the tools!

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5. Understanding the techniques

A basic understanding is necessary

Decision trees

Clustering

Regression

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6. Storytelling

Dont start with the techniques

Begin with the business problem and the outcome.

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(source: vitualspeechcoach.com)

Common pitfalls

Underestimating training needs

On tools

On methods/interpretation

On thought process

Data management

Governance

Not thinking through cultural issues

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Best practices

Build your skills even incrementally

Make sure there are process controls in place before deploying models

Mentors office hours

CoE or even working groups

Collaboration

Model management

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Poll Question

Is democratizing analytics a good idea? Yes, it is best if everyone can build and use models

No, it is too risky to have people who arent trained in analytics using easy to use tools

Dont know

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Making Analytics Simpler: Challenges, Opportunities, and Value

John K Thompson GM Advanced Analytics Twitter: @johnkthompson60

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Collective Intelligence

Native Distributed Analytics

Redefining the Economics of Analytics

Three Forces Redefining Analytics

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Leveraging the analytics skills & abilities of the global community is Collective Intelligence

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The idea is simple, collective intelligence allows for an exchange of ideas, skills, models & more.

Idea & Information

Exchange

Business with a need

$

People with good ideas

$

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Collective Intelligence (CI) the global community.

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CI & Statistica management, security, governance.

Source Model Type Version

CRAN Btree v1.0 CRAN Btree v1.1 CRAN Btree v1.2 AML NN v10 Algo LGR v5.0 Aperv Ensemble V1.0 EM NN V2.0 Experfy CART V3.0

Chicago

Singapore

Sao Paolo

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Native Distributed Analytics - v1.0

Statistica

Statistica Big Data Analytics

Neural Net..

Export Model as: 1. Java 2. PMML 3. C 4. C ++ 5. SQL

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Native Distributed Analytics v2.0

Statistica

Statistica Big Data Analytics

Neural Net..

Export Model as: 1. Java 2. PMML 3. C 4. C ++ 5. SQL

Boomi

Date/Time

Trans type

Velocity

Trigger

JVM

JVM

Private Cloud

JVM

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Native Distributed Analytics v3.0

Statistica

Statistica Big Data Analytics

Neural Net..

Export Model as: 1. Java 2. PMML 3. C 4. C ++ 5. SQL

Boomi

Date/Time

Trans type

Velocity

Trigger

JVM

JVM

Private Cloud

JVM

Statistica Model Building Environment SMBE

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Redefining the Economics of Analytics

Dell set out on one of the most ambitious migration projects since the company was founded.

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Redefining the Economics of Analytics

~300 users migrated ~70% savings in annual renewal fees 300+ projects across multiple business units ~6months

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Start with what you have

Start small

Use the devices and

data you already have.

Build on your current technology investments.

Grow based on real-world success.

Architect for analytics

Plan for analytics-driven action.

Build on your terms with modular, architecture-agnostic solutions.

Harness the power of advanced analytics.

Prepare to scale quickly from pilot to production.

Put security first

Secure from the data

center to the farthest Dell endpoint and along the networks and clouds in between.

Protect data wherever it goes.

Secure for privacy and compliance.

Dells pragmatic approach helps customers get started today.

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Dell Analytics Portfolio

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Data Scientists are scarce, leverage yours and everyone else in the world you can.

Bring analytics to the data, anywhere in the world, at anytime

An open analytics platform will enable this operating model and keep you ahead of the curve and competition.

Key Takeaways

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QUESTIONS?

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Contact Information

If you have further questions or comments:

Fern Halper, TDWI

fhalper@tdwi.org

John K. Thompson, Dell

john.k.thompson@software.dell.com