Advanced Analytics at Scale:Deploying Data Science in the Enterprise

# T C 1 8

Erik Polano

Associate Solution Architect

Tableau

Erwin van Laar

Team Lead, Product Consultancy

Tableau

Session Overview

Agenda

• Bridging the Gap

• Implementation

• Scaling Out

• Q&A

Introduction

Who are we?

MSc Applied Economic AnalysisMSc Public Health: Healthcare Management,

Innovation and Policy

Thesis:

“Fraternity, sorority and stereotyping. A field

experiment examining gender dynamics in referral-

based hiring” presented at American Economics

Association Conference, San Fransisco,2016

Thesis:

“Patient Satisfaction with Care among Patients with

Hematuria”

Oracle, Financial Applications Consultant MaetisArdyn (occupational health service),

Management traineeship and team leader

Loves Linux Loves Theatre

Two worlds……(One Love)

Why is Tableau useful for Advanced Analytics?

Visually Present Results in Interactive Format

Why is Advanced Analytics useful for Business

Users?

Make Better Business Decisions with more informed

analysis

Statistics/Machine Learning Expert Domain Expert

Highly concerned with Validity Highly concerned with Output

Problem

Problem

Experiment

• Ideal World: run double blind controlled experiment

• Causal Impact(Google Data Science team)

• Approximate an experiment using control variables

Problem

• Business users are not trained in (advanced) statistical analysis

• Data Scientists have a critical framework without necessarily having access to what problems are most pressing to their business users

How to Solve This?

Result

• Quicker Development of More Relevant and Informed Analysis.

• Improve ROI on work done by Data Scientists by making their results more visible, understood and relevant to Business Users.

External

Service

Connection

What is the End Goal?

What is the End Goal?

Data-Driven

Experience

People

Time

Want

Can

Conventional Self-Reliant

Want Can

Report Factory

App

Tableau empowers the whole organization. It brings advanced analytics into the hands of people who don’t necessarily have an analyst’s or programmer’s skill set.

Alexs Thompson, Ph.D.

Data Scientist, Hallmark Cards

Bridging the Gap

Visual Analytics v. Advanced Analytics

Visual Analytics (‘viZH(oo)əl ,anə'lidiks)

Data access, discovery, exploration, and information-sharing elevated by visual interactivity.

Advanced Analytics (əd' vanst ,anə'lidiks)

Smart, automated, or otherwise advanced data access, discovery, exploration, and information-sharing, meant to push the boundaries of traditional analytics.

Key Principles

Solutions should have four key characteristics:

• Easy to use

• Fast

• Powerful

• Visual

What do you need?

• Tableau Desktop

• Tableau Server

• External Services• Rserve• TabPy• MatLab

Tableau Desktop

Tableau Server

How could the setup look?

Tableau Desktop Tableau Server End users

Implementation

Implementation Framework

• Discovery

• Prototyping

• Foundation Building

• Scaling Out

Assessing business question/value (Discovery)

• Establish champions from all aligned departments

• Create a Centre of Excellence• Develop and promote best practices

• Provide support

• Promote culture of (advanced) analytics

Prototyping

Model Creation

• Data Discovery Starts.

• Build Presentation of Results through Tableau Desktop

• Calculation types • SCRIPT_REAL, SCRIPT_STR,

SCRIPT_INT, SCRIPT_BOOL

• Calculations are handled as Table Calculations

Connect to Tableau Server

Connect to Tableau Server

tsm configuration set -- key vizqlserver.extsvc.host --value <IP address>

tsm configuration set -- key vizqlserver.extsvc.port --value <Port>

tsm apply-pending changes

Dashboard Design (Foundation Building)

• Use of titles/tooltips

• Guided Analytics

• Interactivity

• Parameters• Selecting the required variables

• Selecting the needed statistical significance

Dashboard Design (Foundation Building)

• Visual cues (design principles)

• Robustness of model

• Can you trust the calculation?

• Use of triggers/shapes/colors

Scaling Out

Scaling out

Two Types:

• Iterative processes across the organization (Number of people involved in building dashboard).

• Availability of Advanced Analytics Dashboards (Number of people consuming the dashboard).

Load Balancing

• HAProxy

• Free, Open Source application for load balancing

• Very useful for scaling out Rserve instances

• Easy to Configure

Tableau ServerHAProxy

Pre-Configuring / Performance

• Heating Up External Environments

• Define How Rserve Should Start

• This can include:• Preloading Libraries

• Create Environments

• Define Timeouts

Can I use both R & Python?

• Flask• Routing requests to either environment

Governance

• Best in Class security and permissions through Tableau Server

• Users

• Groups

• Projects

• Permissions

Continuous Development

• Foster the Centre of Excellence

• Set up fun activities• Organize hackathons

• Makeover Monday

• Set up a Tableau Doctor hour

Questions?

Summary

Summary

• By scripting directly into Tableau, you’re able to:• Perform sophisticated statistical analysis

• Empower end users to set their own parameters and resulting scripts

• Easily and immediately communicate visual results

• Use lessons learned

• Don’t let perfect be the enemy of the good

Summary

• Remember the four key characteristics• Easy to Use, Fast, Powerful & Visual

• Use the framework• Discovery, Prototyping, Foundation Building & Scaling Out

• Get your champions involved

• Create an iterative environment, promote feedback

Conclusion

• Just get out there, and start unlocking more possibilities!

R E L AT E D S E S S I O N S

Tableau + Python = ❤Thur | 10:45pm – 1:15pm | MCCNO - L2 - 217

R…you ready? Jedi stats with R & TableauThur | 10:45am – 1:15pm | MCCNO – L2 – 260

Embedding Tableau for self-service data science

R E L AT E D S E S S I O N S

Thur | 2:15pm – 3:15pm | MCCNO – L2 – 238

Data science applications with TabPy/R

Wed | 12:00pm – 1:00pm | MCCNO – L2 – New Orleans Theater B

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Resources - Whitepapers

Advanced Analytics with Tableau:

https://www.tableau.com/learn/whitepapers/advanced-analytics-tableau

Define Analytics: The changing role of BI’s favorite catch-all term

https://www.tableau.com/learn/whitepapers/define-analytics

Using R and Tableau

https://www.tableau.com/learn/whitepapers/using-r-and-tableau

Resources - Framework

Whitepaper: The Drive Methodology

https://www.tableau.com/sites/default/files/pages/whitepaper_roadforward_lt.pdf

Whitepaper: The Tableau Drive Manual

https://www.tableau.com/sites/default/files/pages/whitepaper_drivemanual_eng.pdf

Resources – Causal Impact

Brodersen, K.H., GALLUSSER, F., KOEHLER, J., REMY, N., & SCOTT, S.L. (2015). Inferring causal impact using Bayesian structural time-series models. Annals of Applied Statistics, vol. 9, pp. 247-274

Blog

https://opensource.googleblog.com/2014/09/causalimpact-new-open-source-package.html

Github

https://google.github.io/CausalImpact/CausalImpact.html

Paper

https://research.google.com/pubs/pub41854.html