characterised by the three Vs…

1. Volume

$\rightarrow$ Size of generated and stored data (e.g. GB, TB)

2. Variety

$\rightarrow$ type and nature of data in in the original unstructured ($=$ to be defined) raw forms. $\rightarrow$ types: seq + time data, data streams, engineering design data, multimedia data, graph and network data. $\rightarrow$ new challenges: how to store + analyse data.

Characteristic data

NoSQL database:

$\rightarrow$ stores data as objects with attributes $\rightarrow$ using object notation language (JSON) $\rightarrow$ VS rational table-based model advantage: set of attributes of each object is encapsulated within the object $\rightarrow$ individual objects can have diff attributes

Data lakes

• a system/repository that con store raw data, as well as processed/transformed data
  • usually as files or ==object blobs== - _collection of binary data stored as a single entr
• can include:
  • structured data from rational databases
  • semi-structured data, e.g. CSV, logs, XML, JSON
  • unstructured data, e.g. emails, documents
  • binary data, e.g. images, video, audio

3. Velocity

$\to$ speed at which data is generated + processed (e.g. real-time)