big data & data science challenges and opportunities

Big Data & Data Science -Challenges and Opportunities

Jose Quesada, PhdDirector

@quesada, @dataScienceRetreat

Personal Background

• PhD in Machine learning, researcher at top labs

• Solving data problems for the last 15 years

• Consultant on ‘customer lifetime value’

• Data scientist at GetYourGuide

• Today, Director at Data Science Retreat

Who is in a data-driven organization?

Who wants to be in a data-driven organization?

“Companies that have embraced a data-driven culture—rating themselves substantially ahead of their peers in their use of data—are three times more likely to rate themselves as substantially ahead of their peers in financial performance” --The Economist Intelligence Unit

x3

http://www.tableau.com/learn/whitepapers/economist-fostering-data-driven-culture

"Many of my clients are clearly aware of the importance of data, But they don't know where to start in terms of where they should focus to get the most value, as well as how to translate the data into actionable insight."

Jerry O'Dwyer, a principal at Deloitte Consulting

http://www.cio.com/article/2387460/business-intelligence/data-driven-companies-outperform-competitors-financially.html

Data Science Retreat mission

“Making sure we

(EU) don’t fall

hopelessly behind

the US when it

comes to

technology”

What challenges are companies facing (B2B, B2C)?

Challenge 1: obtaining data from the end user

Manufacturer

Distributor

Retailer

End user

Manufacturer

Distributor

Retailer

End user

Bad Example: Window maker

• Real company in DE (name omitted)

• No information about what their customers care about• No brand recognition by customers• Exposed to cheaper competitor entering the market any time

Good Example:

Bad Example: textbook publisher

• Real companies (everywhere)• No idea how long it takes for their customer to consume each

page of the textbook

• No information about what their customers care about• No brand recognition by customers• Exposed to cheaper competitor entering the market any time

Good Example:

Challenge 2: Creating a data culture, where data _is_ the core, not a side product

Peter Drucker:...culture eats strategy for breakfast

Challenge 3: Finding talent

Each job ad for data scientist on linkedin gets an average of 150 applicants!

Challenge 4: Open data silos, democratize access to data in the company

Set programs or partnerships in place to make employees more data-literate.

Challenge 5: Big Data hype

You don’t need to have big data to extract value from it. You can make better decisions with your data today. Certainly, you don’t need a Hadoop cluster to start!

Opportunities and actionable advice

1: Measure your company’s data maturity"When was the last time you had to defend forecasts against actuals?“

Identify where you are on the Drake scale for data maturity. Aim to move your company one level up

The Drake scale for data maturity

http://aadrake.com/the-kardashev-scale-of-data-maturity.html

Type 1

Type 2

Type 3

The Drake scale for data maturity

http://aadrake.com/the-kardashev-scale-of-data-maturity.html

Type 1

Type 2

Type 3Staying out of jail.

No data roles

The Drake scale for data maturity

http://aadrake.com/the-kardashev-scale-of-data-maturity.html

Type 1

Type 2

Type 3

Business Intelligence, reporting, or similar team that may use

spreadsheets

The Drake scale for data maturity

http://aadrake.com/the-kardashev-scale-of-data-maturity.html

Type 1

Type 2

Type 3Chief Data Officer or

similar role.Reporting and ad hoc requests previously handled by the BI

team are now part of a self-service

platform so any employee can analyze

the data

2: Identify what value you would like to get out of your dataTypes of value:

• Decrease risk

• Higher precision

• Foster innovation

3: Identify who in the company has the most to gain, form a coalition

Since you need to change the culture of your company (not easy!), every stakeholder you can recruit helps

Recruit people from outside the company if needed

Call to arms!

Data Science is a chaotic field and people don’t really know what they want (much less what they need)

Thank You!Check out our short courses:

Deep LearningScalable machine learning

Big Data Business value---

Jose Quesada, PhDDirector, Data Science Retreat

@datascienceretme@josequesada.com