Big Data Demystifying the Data Scientist

Demystifying the Data Scientist

Dan McClary, Ph.D. Big Data Product Management Oracle

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Data Scientists: By The Numbers

What’s a Data Scientist?

Do I need a Data Scientist?

How do I grow my own Data Scientist?

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2

3


What’s a Data Scientist


What’s Data Science Buzzword or Essential Discipline?

• The buzz around “Data Science” is growing

• But isn’t it a bit like saying “chai tea?”

• What is a functional definition for data science?


A Working Definition

• Data Science seeks to

– Extract meaning from data

– Create “data products”

– Use all available data to tell a valuable story to non-practioners

• So what makes a Data Scientist?


Anatomy of a Data Scientist

Statistical analysis

Scientific training

PhD in Computer Science? Statistics? Physics? Biology?!

Production-grade programmer in Java? Python? SQL

Business sensibility

Visualization

IT Operations Databases

Design Sensibility

Published researcher

BI Tools

Machine Learning Pattern Recognition

Competitive Intelligence Hadoop

Big Data

Excellent Communicator/Presenter Javascript


Anatomy of a Data Scientist

Does anyone like that even exist?


Anatomy of a Data Scientist: Revised

Business

Data Analytics

• Value Proposition • Goals • Communicate

Results

• Techniques • Interpretation • Model

Requirements

• Integration • Manipulation • Quality

Assurance

A person who has some degree of experience in each of


Do I Need a Data Scientist?


Do You Need A Data Scientist?

• Do you need an army of PhDs to solve machine learning problems?

– Probably not

• Could you find more value in the data you do and can collect?

– Undoubtedly

• Do you need people to find that value – Almost certainly


Fitting for Data Scientists

• Where?

– Kaggle.com – a community for Data Science • +100,000 members

– KDNuggets – forum for Data Mining and Data Science

• Who do I hire? – Some call themselves “data scientists,” but most call themselves

• Mathematicians

• Scientists

• Reasearchers

• Physicists

Who? Where? How Many?


Fitting for Data Scientists

• Most organizations will benefit from a few seasoned data scientists

– Help transition to a more data-driven business

– Direct efforts to integrate analytics more tightly with LoBs

– Good understanding of how to tackle new problems

• Data scientists can be grown at home

– Leverage the existing workforce

– Provide growth opportunities for employees

How many do I need?


How do I grow Data Scientists?


Step #1: Find Motivated Individuals

• Developers who want to

– Become more statistically oriented

– Better understand business challenges

• Business Analysts who – Have some programming ability

– Want to grow their technical capabilities

• All candidates should

– Possess tremendous curiosity

– Be able to self-manage

Sources for Good Candidates


Step #2: Find Low-Hanging Fruit

• Find a project that has

– High ROI

– Limited, defined scope

– Isn’t impossible

• Define

– The business value

– The time to invest

Analytically Important, Not Impossible

Val

ue

to B

usi

nes

s

Time to Answer


Step #3: Combine

• Add your data science team

• And the well-defined project

– Add a seasoned data scientist for best results

• Watch the team grow new skills

• Evaluate the outcome

– For the team members

– For the business

And Iterate


Step #4: Publish and Promote Share Data Science Results as a Service

Data Scientist

Useful Derived Dataset

Anyone

Spark


Summary

• What is a Data Scientist

– Someone who can help drive value through data

• Do you need one?

– Possibly

• Can you grow a data scientist – Absolutely


Technology

Big Data Demystifying the Data Scientist