www.ikn.it

Milano, 9 Novembre

2017

FROM A BI APPROACH TO A DATAVIZ APPROACH

Alejandro Vidal

Data Scientist & Designer. BBVA Data Analytics

@doblepensador

Super motivational

Zero practical information

Boring & Technical Talk

This talk

(I hope)

Good to sell phones

A lot of stuff to remember

Not good for humans

Step by step

data visualization is a practice but also a cultural change

How to do it?

organizational structures

Insiders

Specialized (& small?) team inside a bigger one

  • Typical in big companies and data-intensive products
  • Most evident approach
  • Achieve best data visualizations

 

  • Echo chamber effect
  • "Red button" problems
  • We're in the middle: conflict of interest with other areas (developers, designers)
  • What's the optimal size?

organizational structures

Diaspora

Smallers teams inside each area or department

  • Less chamber effect
  • Better integration

 

  • More expensive
  • Client-supplier relationship

organizational structures

freelancing

One-time and focused changes

  • Easiest way for first data visualization uses
  • Cheaper

 

  • There isn't cultural change
  • Hard to create long-term effects

organizational structures

Teacher & evangelist

Long-term and docent approach

  • Scale better in huge companies
  • Focused on cultural change

 

  • More time
  • Open-minded & prepared employees

How to do it badly

If you have enought money and time you can...

  • Start a data visualization project without experts
  • Don't pay attention to collaboration model with other areas
  • Use data visualization at any cost
  • Do it only because other companies do it 
  • Do it because it's cool
  • Do it because it's trendy
  • Do it because it's beatiful

How to do it badly

Well, if you insists... Typical outcomes

Non-sense & chaos

The same but with a graph

"Number decoration"

Data visualization

nice charts

Don't forget the principles

What do you see here?

Same Stats, Different Graphs by Autodesk Research

What do you see here?

Your brain...

Saw a T-Rex

Saw a elliptic pattern

Saw vertical lines

It's pretty amazing finding patterns

USE it ;)

Disclaimer: I studied psychology

You don't need be an expert to make good data visualizations

Every data visualization in the world is...

A function

f(x)

that maps data into images

Data

f(x)

Perception

Insight

Decoding phase

"Data world"

"Visual world"

Encoding phase

COhort

group of clients whicH first purchase was in one specific month

January cohort: clients who purchases its first product in January

 

February: client who purchases its first product in February

...

Data

f(x)

Agressive campaings are not as great as they seem

auto experimentation

Use your own business questions to detect which design is better

My question is: 

When this KPI gets its lowest value?

auto experimentation

Business question: 

What product is my best-seller?

find the human in the loop

End users

send invoices

mailbox

Accountant

process the invoices

writes

reports

gives advice

checks

notifies

errors

Auditor

Try to find the human in the loop

There could be an oportunity for data visualization!

Identifying the user is 50% of knowing his needs

BBVA Personal FINANCIAL MANAGEMENT

BBVA users

BBVA

Personal Advisor

BBVA

How can we improve the experience for users without personal advisor?

Data visualization ;)

(& artificial intelligence)

Typical Questions when i explain this

My data is too simple to use data visualization

There is no dataviz application in my loops

If it's simple KEEP IT SIMPLE

Airbnb's search interface

Airbnb's host insights system

IF THere isn't Create new loops

contracts

Point of Sale

pay with

Retailer

Think outside the box

communication, ART & Science

Communication

(The human in the loop is general public)

Art

t-SNE Map Artworks

Google Arts Experiments

By Cyril Diagne, Nicolas Barradeau & Simon Doury

SCIENCE

Artificial intelligence has "Black box models"

SCIENCE

EMBEDING PROJECTOR

by Google

You're seeing the 100 most similar words to "politics" based on a Natural Language Processing Algorithm

"Bad"

"Good"

SCIENCE

EMBEDING PROJECTOR

by Google

SCIENCE

Step by step

Don't forget the principles

the human in the loop

Prepare your organization for this change

These are core. Forget them and you'll get bad products

Design with your user in mind

www.ikn.it

Milano, 9 Novembre

2017

GRAZIE PER L ’ATTENZIONE

Alejandro Vidal

Data Scientist & Designer. BBVA Data Analytics

 

@doblepensador

alejandro.vidal@bbvadata.com

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