Backstage to Data Driven Culture

Success with an Agile Data Science

Stack

Big Data LA Day 2016 Pauline Chow

Desi Medoza @ Unsplash

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So, You are the First Data Scientist…?

WORLDWIDE BUSINESS BUSINESS TO GO CREATIVE SOLUTIONS

WORLDWIDE BUSINESS BUSINESS TO GO CREATIVE SOLUTIONS

What my Friends Think I Do What my Mom Thinks I Do What Society Thinks I Do

What my Boss Think I Do What I Think I Do What I Actually Do

Misconceptions about Data Scientists

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So, You are the First or Lead Data Scientist…?

Open Source & New Tools

Profits Steady , Adding Products

Report to VP Marketing

Non Technical Culture

First Data Scientist

What does the organization do

best? How does it relate to data and technology?

What is the business core competencies?

What are existing tools,

processes, and code? Do you have a budget for new tools and

resources?

What Tools are Available ?

This is both a team members

and expectations related question.

Where is your Team?

What is the mood of the organization? How are they solving problems? Why are they adding DS/A into the organization?

What is the State of the Organization?

Who are the stakeholders? How is data able to contribute to their goals and expectations?

Who has the Influence On the Roadmap?

Context for Presentation

Case Study: Startup in Digital Media

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Effectively Implement Solutions

Maximize Impact & Commun- ication

Set a Blueprint that promotes flexibility,

iteration, and scalability. It facilities

agile-oriented mindsets for data

practices and it crucial for implementation.

Build a Roadmap from Blueprint to

shape data practices and implement goals from stakeholders,

company, as well as strong DS/A foundations.

Develop key qualitative and

quantitative milestones.

Communicate consistently and frequently to the

organization.

Influence

Expectations

Influence from both angles, yours and

stakeholders expectations. Find explicit and implicit

goals and bridge the gaps that you find.

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Key Drivers Integrating Data Culture

Create an Agile Data Science Stack

Non-technical focused

Actively Listen

Implement

Explore Collaborate

Influence Grow

Guiding Verbs for “First” Data Scientist

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In no particular order

ACTIVE LISTENING:

What Are you Trying to Hear?

Explicit Goals & Expectations Structured, straight-forward, logical, and safe inquiries Document, share, and openly discuss with team members and stakeholders.

Jungwoo Hong @ Unsplash

Implicit Goals & Expectations

Thom @ Unsplash

IMPLEMENT:

HOW TO APPROACH YOUR BLUEPRINT FOR DATA

DRIVEN-INFORMED CULTURE?

Architecture First

Process First

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STACK AGILE APPROACHES

Anthony Delanoix @ Unsplash Jeff Sheldon @ Unsplash

Blueprint approach from infrastructure perspective

AGILE BY ARCHITECTURE

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Customize as the team grows

SaaS & PaaS Integration

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IDENTIFY

BUILD SYS & MODELS

- Select Appropriate Models - Build Models and Pipelines for Scalability - Evaluate and refine Models

ACQUIRE DATA

- Identify the “right” source - Import data and set up remote / local storage - Determine tools to work with selected sources

CREATE PROBLEM STATEMENT

- Identify business, data, product objectives - Brainstorm potential solutions - Create questions and identify people/stakeholders to help

PARSE & MINE DATA

- Determine distribution of data and necessary transformations - Format, clean, splice, etc - Create new derived data

PRESENT RESULTS

- Summarize Findings - Add Storytelling aspects - Identify next questions and additional analysis - For teams and stakeholders

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AGILE BY PROCESS Blueprint approach from workflow perspective

ACQUIRE PARSE & MINE PRESENT BUILD DEPLOY

IDENTIFY

BUILD SYS & MODELS + DEPLOY

Leverage platforms that document models, pipelines, and feature iterations. Collaboration is a plus.

-  Sklearn pipelines -  DS/ML platforms: Yhat,

domino labs, anaconda

ACQUIRE DATA Curate data from existing sources that is cleaned, reliable, and automated, where ETL can be skipped

-  Segement.io -  Zapier -  CrowdFlower -  Open Data

CREATE PROBLEM STATEMENT

Keep most attributes of this section in-house and within your team

PARSE & MINE DATA

For the data that cannot be automated or acquired cleanly, sklearn pipelines or open source Luigi (Spotify) or airflow (AirBNB) can mitigate this process.

PRESENT RESULTS

Adopt platforms that allow for iterations and data mining/parsing process to feed into reports and presentations

-  Ipython Jupyter Notebooks

-  Dashboards: Looker, RJMetrics, Tableau

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SaaS & PaaS Integration Customize as the Process Increases in Complexity

ACQUIRE PARSE & MINE PRESENT BUILD DEPLOY

COLLABORATE:

What Metrics to Emphasize for Teamwork?

Burn Rate Most companies do not widely

broadcast but transparency can put decisions into perspective for the

organization. Time and urgency can also be of the essence. Customer

Acquisition Cost (CAC)

Illustrates market competitiveness with your products, services, and market saturation. Social media ad platforms can make up a large portion of these costs.

Gross Profit &

Revenue Actual revenue & profit after

expenses, investors, and ongoing costs. If the business model and product are viable then the company will be able

to stand on its own without external capital.

Active Users Measure the ongoing stickiness of a service or product. Clearly define “active” to not overcompensate first-time, new, and experimental users. Can the company move beyond early adopters and fans?

Churn Rate & Retention

How many people are leaving or become inactive after a certain

period of time? When in the customer’s lifetime is churn more

likely to occur? The higher the expected churn rate, then the

more the company has to spend on acquiring new customers.

Cumulative Growth Cumulative growth puts a long term and sustainable perspective to just month over month growth. Short-term growth can unabashedly take over and cause decision makers to lose sight of an organization’s mission and goals.

Response Time

The amount of time teams take to respond and complete tasks,

which includes bug fixes, technological improvements,

product upgades, and customer service. Responsiveness

demonstrates staff and team dedication, effective allocation of

resources, operational effectiveness, and no tech debt.

Customer LIfetime Value (CLV) Total dollars from a customer during the lifetime relationship with that customer. Intersection of frequency of customer purchases, revenue per customer, acquisition costs. This measure can have predictive qualities

INFLUENCE

How to align and connect goals and expectations?

"Leadership is the art of giving people a platform for spreading ideas that

work."

-Seth Godin

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Evaluate milestones, iterate and grow

Month 12 Blueprint for Agile Data Science and

Analytics Stack

Day 30 Establish clear

measures for success as widespread as

possible

Day 90

Good first impressions. Listen

and Learn!

Day 1 Celebrate improvements

to workflow, effectiveness, and

access

Day 60

Democratize data access and streamline measures to external and internal teams

Month 6

Communicate, Strategize, Communicate...

Connect the Dots

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Anything Else Reporting & Urgent

Requests

Data Acquisition,

Cleaning Exploration &

Analysis, Reports, &

Presentation

20% 80% 80% 20%

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Allocate Time & Resources Effectively

Business as Usual Allocation New Data Science Allocation

GROW YOUR TEAM

When to increase the ability and capabilities of your team?

Technical Project Manager

Data Scientist

Data Engineer

Data Engineer

Analyst Researcher

Team Members

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1

2 5 Central to the ability to juggle and balance

responsibility of being the first/lead data scientist.

Agile Data Science & Analytics Stack

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4 Active Listeni

ng

Influence

Collaborate with Metrics

Explore

Implement

Grow

Actionable Agile DS/A Stack is Key to Success

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@DataThinker WhenThereIsData.com

pauline.chow@gmail.com