101: Why Data Science?

What is Data Science?

  • Software Engineering, Maths, Automation, Data

  • A.k.a: Machine Learning, AI, Big Data, etc.

  • It’s current rise in popularity is due to more data and more computing power.

For more information: https://winderresearch.com/what-is-data-science/


Examples

US Supermarket Giants

  • Target: Optimising Marketing using customer spending data.

  • Walmart: Predicting demand ahead of a natural disaster.


Discovery

  • Most projects are “Discovery Projects”.

  • Primary Business goals: Increase Revenue, save costs, save time.

  • Budgets can come from other parts of the business.


Automation

  • The automation of tasks is a wider trend within industry.

  • Software Engineering is the automation of processes.

  • Data Science is the automation of decisions.

  • Data Science offloads the burden of a decision to an automated process.


Data Science is an Asset

Good Data => Good Data Science => Good Decisions

More examples

  • Signet Bank

  • Amazon, Google, Facebook, et. al.

  • Caesar’s Entertainment.


The Job Market

Global Engineering shortage.

In 2017 the UK engineering sector requires 100,000 graduate-level engineers per year. 40k are UK nationals. 40k are foreign nationals. 20k deficit.

The state of engineering, Engineering UK, 2017

  • Hampering the UK’s presence in global engineering
  • Brexit?
  • Hard to get more detailed numbers.

Data science:

  • UK: “Rare as unicorns” - Guardian
  • US: 100,000 shortage - Gartner
  • US: 140,000-190,000 shortage - McKinsey
  • US: 181,000 needed by 2018 (IDC)

Big numbers, but take with a pinch of salt.

  • UK Median salary: £65k, vs. £45k for all of IT Source

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