Big Data Flashcards
What is the definition of Big Data?
Large volumes of extensively varying data that is generated and processed at high velocity.
How is Big Data becoming increasingly troublesome in IS/IT?
It cannot be easily stored on a single computer or sent over a firm’s network. How do we analyse?
Give some examples of Big Data sources:
Loyalty cards, online transactions, tracking systems, healthcare, social media, image metadata.
What are the three Vs of Big Data with examples?
Volume: Large Hadron Collider generated 13 PetaBytes of data in 1 year.
Velocity: Users demand real-time services - on-demand video generates 100 billion personalised suggestions every week.
Variety: text, images audio, 3D on social media.
What is Data Analytics?
Using software to analyse data to answer: Why are there differences between groups?, Why is this?, How can I improve in this respect?
How might business analytics be used in a business context?
Gain information to make more profit and lower overheads (Can give generic examples)
What is multi-level analysis?
Looking from small specific trends to large trends. i.e. From an individual to whole market.
Give some examples of questions Big Data Analytics can answer:
What are we doing well and how do we maintain this?
What are we doing badly and how can we fix this?
How are competitors doing?
How did competitors get to where they are?
Forecasts.
What must you think about when performing analytics?
Who are the observers and what do they want?
How often do analytics need to be carried out (Frequency)?
What exactly do we want to know?
Expand on observers and what they want:
Which stakeholder is the analysis for? What would they like to know (e.g. how to increase sales)
Expand on frequency:
For example should the frequency be seasonal (clothing industry). Or minute by minute as it might be when food shopping. How can more be sold.
Expand on what we want to know:
Sales? Profit? Waste? Costs? etc.
How do you want to implement the results? e.g. marketing, new products, changing prices etc.
What is ‘actionable insight’?
It is results from big data analysis that provides what was required (insight) and how to achieve it (actionable).
Give the basic systematic analytic strategy:
Observer needs -> Focal ‘thing’ -> Obtain data -> analysis and action -> Observer needs…
Give a scenario where actionable insight is typically used in the consumer industry:
Reactivation or re-engagement of customers. Using big data analytics to find a way to make customers return to your business. e.g. personalised ads or amazons repeat purchase option for things that run out e.g. glue.
