Tweet
Tweet

Slide 1

Slide 1 text

How can Data Science benefit your business? Peadar Coyle Data Analytics Consultant @springcoil

Slide 2

Slide 2 text

My Experience My Experience Expert in Big Data Technologies and Data Science Mathematician by training - specialized in Machine Learning Supply Chain Management Customer Churn optimization for B2B in the Pharmaceutical industry Customer Segmentation for Event Management at Letsface.cn Sentiment analysis for a large financial consultancy Web crawl data analysis at Import.io

Slide 3

Slide 3 text

I did Data in Shanghai I did Data in Shanghai Helping an event website target its customers

Slide 4

Slide 4 text

Data in London Data in London Data geeks need tools like these, I helped launch the beta.

Slide 5

Slide 5 text

I worked with Data in Luxembourg I worked with Data in Luxembourg For a small e-commerce website. Doing Supply Chain models.

Slide 6

Slide 6 text

Now I work with Now I work with Data in Luxembourg @ Data in Luxembourg @

Slide 7

Slide 7 text

In Air Traffic Management In Air Traffic Management BTW Air travel produces A LOT of data!

Slide 8

Slide 8 text

So how come I care about data? So how come I care about data? Well I always loved science. Well I always loved science. I wanted to be a neuroscientist I wanted to be a neuroscientist

Slide 9

Slide 9 text

Then I fell in love with Physics Then I fell in love with Physics I studied Quantum Mechanics and I studied Quantum Mechanics and Quantum Optics at Bristol Quantum Optics at Bristol

Slide 10

Slide 10 text

This gets a bit complicated... This gets a bit complicated... And my cat was never much use... And my cat was never much use...

Slide 11

Slide 11 text

So I ended up in Math & Stats... So I ended up in Math & Stats...

Slide 12

Slide 12 text

Along the way I learned some Along the way I learned some programming and other skills... programming and other skills...

Slide 13

Slide 13 text

I needed to find a career I needed to find a career And I decided Academia wasn't for me. And I decided Academia wasn't for me. So I became a data scientist! So I became a data scientist! Now what skills does a data scientist have? Now what skills does a data scientist have?

Slide 14

Slide 14 text

No content

Slide 15

Slide 15 text

To me data Science is a lot like Science To me data Science is a lot like Science

Slide 16

Slide 16 text

But the hardest thing to learn has been.. But the hardest thing to learn has been.. “Being a data scientist is not only about data crunching. It’s about understanding the business challenge, creating some valuable actionable insights to the data, and communicating their findings to the business.” Jean-Paul Isson, Monster Worldwide, Inc.

Slide 17

Slide 17 text

I'm still learning the tech stuff too I'm still learning the tech stuff too What is Machine learning? What is Machine learning? Well this next slide might help... Well this next slide might help...

Slide 18

Slide 18 text

No content

Slide 19

Slide 19 text

What is Data Science? What is Data Science? Data Scientists help you harness the Data Scientists help you harness the value of 'big data' value of 'big data'

Slide 20

Slide 20 text

So, who is talking about Big Data? So, who is talking about Big Data? "We project a need for 1.5 million additional managers and analysts in the United States who can ask the right questions and consume the results of the analysis of Big Data effectively." - , McKinsey report Big data: The next frontier for innovation, competition, and productivity

Slide 21

Slide 21 text

Who else? Who else?

Slide 22

Slide 22 text

Gartner says 'Data is the new oil' Gartner says 'Data is the new oil'

Slide 23

Slide 23 text

'Data are becoming the new raw material of business'

Slide 24

Slide 24 text

But talk is cheap... But talk is cheap... Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it... - Professor Dan Ariely - Duke University

Slide 25

Slide 25 text

So how do you get value out of your So how do you get value out of your data? data?

Slide 26

Slide 26 text

You could hire a data scientist You could hire a data scientist This talk is aimed at helping you understand if you This talk is aimed at helping you understand if you need to hire a 'data scientist'. need to hire a 'data scientist'.

Slide 27

Slide 27 text

Aims of the talk Explain the substance behind the phrase 'big data' Tell you how you can use data in your business. Help you understand the importance of data in your business strategy.

Slide 28

Slide 28 text

Or this talk could have been titled... Or this talk could have been titled... But Peadar where are the business But Peadar where are the business examples? examples?

Slide 29

Slide 29 text

No content

Slide 30

Slide 30 text

Example: Linkedin Example: Linkedin

Slide 31

Slide 31 text

But I work in the real world not online! But I work in the real world not online! UPS uses data to travel more efficiently and save millions on fuel consumption.

Slide 32

Slide 32 text

What is "Big Data" anyway? What is "Big Data" anyway? Customer peference data is...

Slide 33

Slide 33 text

What is "Big Data" anyway? What is "Big Data" anyway? Wind sensor data is too Wind sensor data is too 'Source: English Wikipedia, original upload 15 July 2004 by - Creative Commons Sharealike license Leonard G.

Slide 34

Slide 34 text

What is "Big Data" anyway? What is "Big Data" anyway? Web crawling data is too

Slide 35

Slide 35 text

What is "Big Data" anyway? What is "Big Data" anyway? Audio and visual data is too

Slide 36

Slide 36 text

What is "Big Data" anyway? What is "Big Data" anyway? Social Media data must be too

Slide 37

Slide 37 text

What is "Big Data" anyway? What is "Big Data" anyway? Not to mention social media metadata

Slide 38

Slide 38 text

Genomics and health data are too. What is "Big Data" anyway? What is "Big Data" anyway?

Slide 39

Slide 39 text

And what about Particle Physics data? What is "Big Data" anyway? What is "Big Data" anyway?

Slide 40

Slide 40 text

I hope you can see that there is... I hope you can see that there is...

Slide 41

Slide 41 text

Remember this slide? Remember this slide?

Slide 42

Slide 42 text

So why good data analysis is hard? Getting data is hard Building models is hard Asking the right business questions is even harder I often have to borrow lots of peoples brains to get to the right business questions...

Slide 43

Slide 43 text

Pick the right methodology for the job Pick the right methodology for the job Text -> topic modelling, sentiment analysis, information extraction E-commerce data -> prospensity analysis, collaborative filtering Multimedia -> speech-to-text, audio fingerprinting, face recognition Clickstream logs -> frequent pattern mining, sequence analysis Proton-proton collision from LHC -> I have no idea despite having a Physics degree

Slide 44

Slide 44 text

And then what? Well you can tell stories with visualizations...

Slide 45

Slide 45 text

But Data Scientists don't just produce reports They produce data products too. So what is a data product? Well I'm glad you asked...

Slide 46

Slide 46 text

What is a data product? What is a data product? A data product provides actionable information without exposing decision makers to the underlying data or analytics. Examples include: Movie Recommendations, Weather Forecasts,Stock Market Predictions, Production Process Improvements, Health Diagnosis, Flu Trend Predictions, Targeted Advertising. – Mark Herman, et al., Field Guide to Data Science

Slide 47

Slide 47 text

But you said... But you said...

Slide 48

Slide 48 text

Here is an Example from Mailchimp: Here is an Example from Mailchimp: When should I send that email? When should I send that email?

Slide 49

Slide 49 text

Step 1 to 100: Data Scientists - do lots of Step 1 to 100: Data Scientists - do lots of analysis... analysis...

Slide 50

Slide 50 text

And produce a magic button :) And produce a magic button :)

Slide 51

Slide 51 text

Define Data Science Define Data Science It is the application of science and models to really complex human problems Such as: Who is buying our product, why are they leaving our service. Data scientists leverage mathematics and computer science to deliver business value such as smoother operations, enhancing your marketing strategy or forecasting supply and demand. In short data scientists help you prepare for the future.

Slide 52

Slide 52 text

How does this help you in your business?

Slide 53

Slide 53 text

No content

Slide 54

Slide 54 text

Case Study - Marketing Analytics: In Case Study - Marketing Analytics: In the Game Industry the Game Industry 1) Uses gamers play data to optimize marketing communications across channels. - Customer segmentation modelling 2) Building Personalization Engine Rules for 1:1 communications with individual gamers. To help reduce customer churn. 3) Predicts gamers likelihood to churn or to respond to up-sell offers.

Slide 55

Slide 55 text

Example Example Here is a graph of active users on an online game. Marketing teams use tools like this to monitor their customers in real-time

Slide 56

Slide 56 text

What about forecasting? Do you mean the weather? What about forecasting? Do you mean the weather? (In Ireland and the UK it is quite easy - just guess rain (In Ireland and the UK it is quite easy - just guess rain all the time!) all the time!) But there are other kinds of forecasts such as supply But there are other kinds of forecasts such as supply chain forecasts or demand forecasts.... chain forecasts or demand forecasts....

Slide 57

Slide 57 text

Example:Supply Chain Management Example:Supply Chain Management These are examples from Tableau an excellent data science product - based on laptop sized data sets. Similar to my Amazon work. However these can also be built with open source tools.

Slide 58

Slide 58 text

But predicting the future is hard But predicting the future is hard "It’s Difficult to "It’s Difficult to Make Predictions, Make Predictions, Especially About Especially About the Future" - the Future" - Niels Bohr Niels Bohr

Slide 59

Slide 59 text

And let data be your guide. So you can do an experiment So you can do an experiment

Slide 60

Slide 60 text

User Conversion after a website change. User Conversion after a website change. Luckily they measured it. They learned the website Luckily they measured it. They learned the website change was a bad decision. change was a bad decision.

Slide 61

Slide 61 text

Sometimes in life you just need pictures Sometimes in life you just need pictures or data visualizations, like this... or data visualizations, like this...

Slide 62

Slide 62 text

Or this: Number of wind turbines by state in the US? Or this: Number of wind turbines by state in the US?

Slide 63

Slide 63 text

But this is Luxembourg... But this is Luxembourg... So we need finance examples... So we need finance examples...

Slide 64

Slide 64 text

Example: Financial Analysis Example: Financial Analysis

Slide 65

Slide 65 text

Example: Moving average of AAPL Example: Moving average of AAPL

Slide 66

Slide 66 text

Especially with changes in regulation... Risk is also data science challenge Risk is also data science challenge

Slide 67

Slide 67 text

But I don't work for a corporation But I don't work for a corporation Data can be used for NGOs too...

Slide 68

Slide 68 text

Data can be used for NGO's Data can be used for NGO's This is a web app of house prices and commutes, done for an NGO in London who wanted to show the effects of changes in house prices on peoples commutes.

Slide 69

Slide 69 text

Reducing Maternal Mortality Rates in Mexico Reducing Maternal Mortality Rates in Mexico - - Mexico - Presidencia de la Republica Mexico - Presidencia de la Republica The maternal deaths in Mexico from pregnancy, childbirth or postpartum complications have decreased from 89 deaths per 100,000 live births in 1990 to 43 in 2011. Despite this improvement, the rate of decline has significantly slowed and Mexico is not on track to achieve its Millennium Development Goal of reducing maternal mortality 75% by 2015.

Slide 70

Slide 70 text

But what if you're in Politics? But what if you're in Politics?

Slide 71

Slide 71 text

Earlier I showed how data can Earlier I showed how data can even predict 49 out of 50 states even predict 49 out of 50 states in the last American election. in the last American election. And that Obama would be the president!

Slide 72

Slide 72 text

So why would I need a data scientist? So why would I need a data scientist? You may already have one. I know numerous business intelligence, data analysts, business analysts, risk analysts who ARE data scientists. Alternatively you can hire a data analytics consultant to help you get started. But what signals should I look for? Well there are many answers... Like...

Slide 73

Slide 73 text

Does this sound like you? Does this sound like you? Are you not taking full advantage of your reporting? Are you not taking full advantage of your reporting? Do you need a high level visual overview of your Do you need a high level visual overview of your operations? operations? Are you targeting your marketing efforts effectively by Are you targeting your marketing efforts effectively by using the right customer segmentation - by age or using the right customer segmentation - by age or gender for example? gender for example?

Slide 74

Slide 74 text

Or this? Or this? Are you losing customers and not understanding Are you losing customers and not understanding why? why? Are you making decisions on the basis of data or on Are you making decisions on the basis of data or on the basis of 'gut feeling'? the basis of 'gut feeling'? Are you changing your websites or products on the Are you changing your websites or products on the basis of data driven experimentation? basis of data driven experimentation?

Slide 75

Slide 75 text

Example: What-if analysis... Example: What-if analysis...

Slide 76

Slide 76 text

What about communication? What about communication? Mathematically sound communication to clients: you may have situations where you need the data scientists to talk directly to clients or to their data scientists. This is yet another reason to make sure you hire someone with excellent communication skills, because they will be representing your business to really smart people.

Slide 77

Slide 77 text

Data Scientists are like 'translators' Data Scientists are like 'translators' A lot of my work at the moment is mathematical communication with external stakeholders and Professors. At Amazon a lot of my work was with Research Scientists in Optimization. Translating their ideas for business stakeholders. I often have to translate from the 'business' to the 'software' team. Do you have someone like that on YOUR team?

Slide 78

Slide 78 text

If this sounds familiar If this sounds familiar then you might need then you might need to hire a data scientist! to hire a data scientist!

Slide 79

Slide 79 text

I hope the examples helped I hope the examples helped I hope it is also clear how data can be used in whatever field you work in. I hope it is also clear that 'big data' is not something to be scared of but should be part of your organizations strategy. I know that developing a data-driven culture is extremely difficult.

Slide 80

Slide 80 text

Thank You For Listening Thank You For Listening Any questions? Reach out to me if you have any data questions. @springcoil Search Peadar Coyle on Linkedin [email protected]