1. How Can Engineering Take Data Sciences from Ideas to Action
By Adam Stallard

2. How Can Engineering Take Data Sciences from Ideas to Action
What is Data Science
The Data Scientists
Scientists vs. Engineers
A Real Life Example – The Idea
Roles
Into Action
Demo

3. What is “Data Science”? big data business analytics mathematics
probability models
machine learning
statistics
data analytics
business analytics
programming
data engineering
visualization
data warehousing
insight

4. The Data Scientists

5. Skill Overlap big data business analytics mathematics programming
probability models
machine learning
statistics
data analytics
business analytics
programming
data engineering
visualization
data warehousing
insight

6. Scientists vs. Engineers

7. Scientists theoretical physics
explore the natural world with theory and practical experiments
discover and expand knowledge
provide information and knowledge for the engineers
use tools/application built by engineers

8. Engineers robotic engineering
Apply (scientific) knowledge to solve problems
development and/or improvement of product or processes
optimise, efficiency are key (cost, tools etc)
guide others on processes and procedure

9. Scientists vs. Engineers
“In engineering you do not start a project unless you know the answer while in science you do not start a project if you know the answer.”

10. The Idea: A Real Life Example

11. Idea (aka Business Question)
Does the early opinion of Morpheus match our segmentation of potential buyers?

12. Role of the Data Scientists
gather requirements from stakeholders
prepare any existing usable data models
natural language processing in R/Python/etc
liaise with various team members – Data Science Engineers
analysis of data / presentation of outcome
attend meetings

13. Role of the Data Science Engineers
gather requirements from Data Scientists
prepare any existing applications/processes or develop new ones
decide and research on best solution for the task
retrieve, profile, clean and integrate data
automation of repetitive tasks – make life easier
liaise with various stakeholder
attend meetings

14. Data Scientist Requirements
Brief / Requirements:
download user posts/comments from social networks and dedicated gaming websites to analyse
data in csv format or integrated to data warehouse
set parameters, including but not limited to website and filter comments
mobile – can be used anywhere with the correct authentication etc.

15. Data Science Engineers Into Action
What the DSE will be developing:
- create a website/comment scraper – modular and scalable
- comments logged to a database
- interface allows users to set parameters
- application hosted on web server

16. Data Science Engineers Sprint Into Action

17. First Sprint
research
develop script for reddit comment scrapping
log reddit comments to mysql database
start application via web interface
comment output

18. Data Science Engineers – Tools of the Trade

19. What Was Built - Application Demo bmxgamer. coeus. feralhosting
What Was Built - Application Demo bmxgamer.coeus.feralhosting.com/flask/

20. What Was Built - Application Demo bmxgamer. coeus. feralhosting
What Was Built - Application Demo bmxgamer.coeus.feralhosting.com/flask/

21. Just for Fun

22. Sprint Review
Your thoughts?
What would you improve?
Tasks for the next sprint?

23. Thank you for Listening
Any Questions?