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Every day we create 2.5 quintillion of data

90% in the last two years

x40 in 2020

Big Data

How to dealing with it!

The 5 V’s

• Volume: How much data should you really be measuring?
• Variety: How many different kinds of data do you actually need / from how many channels (and how much of it is actually useful)?
• Velocity: How fast is your customer data travelling?
• Veracity: Is your data accurate?
• Value: Capturing valuable data is important, but make sure that you are creating more value for your customers than you are capturing.

Google Data Center

Cloud Computing

Machine Learning

Maths

Statistics

The result:

• Improve competitivity
• Data-driven decisions
  • Describe reality of your company
  • Predict behaviour of your clients
  • Innovate with new business solutions
• Real time
• What if, simulate alternatives

For example…

Emotion Recognition

Sports Data

Netflix

Artwork Personalization

The born of a new science

The evolution of statistics and computer science are combined to extract meaning of data, to build complex models and to solve real needs providing a new field of study: Data Science.

Specific requeriments:

Data Science history

• 1996: term “Data Science” first time used by the members of IFCS in one of their conference.
• 2002: first data science journals began to be launched: such as the Data Science Journal, or the Journal of Data Science.
• 2009: Hal Varian, Google’s Chief Economist, in an interview to McKinsey Quarterly, named data scientist as the sexy job in the next ten years

Hal Varian’s Interview

“I keep saying the sexy job in the next ten years will be statisticians. People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s? The ability to take data-to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it-that’s going to be a hugely important skill in the next decades. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it.”

Data Scientist as a job

It’s the top demmanded profile in United States!

Skills of a data scientist

But…what they really do?

Don’t confuse!

• Data Engineer: Expert in data arquitecture, systems and software engineering.

• Data analyst: Expert in the subject and tell a story with data, but not necessarilly in machine learning

• Database administrator: Expert in store and organize data

“If you torture the data long enough, it will be confess.” – Ronald Coase, Economics Nobel Prize

Inspired by…

• Data Speaks, Data Stories that matter - LUCA, Telefónica
• Big Data, conviviendo con el algoritmo - Documentos TV
• 10 Key Marketing Trends for 2017 - IBM
• Artwork Personalization at Netflix
• Data Scientist: The Sexiest Job of the 21st Century - Harvard Business Review