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