Data Science Definitions

Question 1

What is the analytical difference between Data Science and Business Intelligence?

Answer 1

BI = descriptive methodology to data/information. Kimball - users of BI system watch the wheels of an organisation turn to eval performance.

DS = emphasis on predictive and prescriptive methods to uncover patterns in the data. What patterns satisfy this data?

Question 2

Does Data Science favour an inductive or deductive approach?

Answer 2

DS can be said to favour an inductive, scientific approach to the analysis of data, as opposed to the more deductive methods of BI.

Question 3

What types of data does Data Science work on?

Answer 3

Unlike BI which relies on well understood structured data held in Data Warehouses, DS works on both un/structured data, that is less predictable and is highly variable

Question 4

What skills does a BI practitioner require?

Answer 4

Skills in sourcing tabular data, reformatting and integrating into DW. Analytical techniques such OLAP

Question 5

How does a Data Scientist skills differ from BI?

Answer 5

Needs to have some BI skills/Data Engineer skills, but focus more on hypothesis and experimentation with data. Extract meaning from/interpret data using stats and ML to find patterns and build models.

Question 6

What is datafication?

Answer 6

The process of taking all aspects of life and turning them into data

Question 7

What is a Data Scientist?

Answer 7

Someone who knows how to extract meaning from data and interpret data, which required tools from ML and Stats.
Needs to collect/clean data; EDA; prep data for modelling; modelling; evaluation; present findings.

Derive the business questions.

Question 8

How would you describe Data Science?

Answer 8

Data Science is a cross-disciplinary subject comprising: skills of a statistician who knows how to model and summarize datasets; skills of a computer scientist who can design and use algorithsm to store/process/visualise data; domain expertise - necessary to formulate the right questions and put the answers in context.

Question 9

Describe the interaction btw Data Science, Machine Learning and AI.

Answer 9

Data Science can be seen as a discipline that encompasses ML along with Statistics, Data Viz, Data Mining.

Machine Learning is both a sub-field of AI, and a component in many other AI fields such as Computer Vision, Robotics

Job roles now: Data Scientist, Machine Learning Engineer, Data Engineer

Question 10

** Take some notes from 2017 semester 1 BI SYStems notes **

Answer 10

TBC