Week 2 - Visualisation for Decision Making Flashcards
(10 cards)
What are the five characteristics of Big Data?
Volume, Velocity, Variety, Veracity, Value
Each characteristic addresses a specific aspect of Big Data.
Define the ‘Volume’ characteristic of Big Data.
Data at rest, terabytes to exabytes of existing data to process
Volume refers to the scale of data storage.
Define the ‘Velocity’ characteristic of Big Data.
Data in motion, streaming data requiring milliseconds to seconds to respond
Velocity emphasizes the speed at which data is generated and processed.
Define the ‘Variety’ characteristic of Big Data.
Data in many forms: structured, unstructured, text, multimedia
Variety refers to the different types of data formats.
Define the ‘Veracity’ characteristic of Big Data.
Data in doubt, uncertainty due to inconsistency, incompleteness, ambiguities, latency, deception, model approximations
Veracity highlights the trustworthiness of the data.
Define the ‘Value’ characteristic of Big Data.
Data into money, business models can be associated with the data
Value indicates the economic worth derived from data.
What does data slicing in data cubes allow?
Different views/perspectives of the same data by selecting combinations of occasions, entities, and characteristics
Data slicing helps in analyzing data from various angles.
What are elementary questions in data analysis?
Result in a single value, e.g., bread sales today
Elementary questions focus on specific data points.
What are intermediate questions in data analysis?
Result in several values, e.g., bread sales over the past 3 days
Intermediate questions provide insights over a defined period.
What are overall questions in data analysis?
Answered by the whole data set, e.g., bread sales trend over all days
Overall questions summarize data trends and patterns.
