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PART C: ACCOUNTING AND REPORTING SYSTEMS, CONTROLS AND COMPLIANCE 
 
262
 
7.2.2 Big data and data analytics
The advent of technologies such as social media and smart phones mean that organisations are 
increasingly able to access 
vast amounts of data
. This data may be in various forms (for example, 
numbers, words, pictures, videos and phone messages) and may originate from both inside and outside 
the organisation and is commonly known as big data.
Big data originates from a number of sources: 

 Processed 
data
– originating from existing databases of business and other organisations. 

 Open 
data
– originating from the public sector data (for example transport, government financial 
and public service data). 

 Human-sourced 
data
– originating from social networks, blogs, emails, text messages and 
internet searches. 

 Machine-generated 
data
– originating from fixed and mobile sensors, as well as computer and 
website logs 
Big data has 
four characteristics
. 
Characteristic 
Description 
Volume 
This refers to the quantity of data that is available. Big data is available 
relatively easily and in vast quantities. 
Velocity 
This refers to the speed at which big data can be streamed into the 
organisation. Big data is often available to an organisation in real time 
rather than over longer periods such as on a weekly or monthly basis.
Variety 
Variety concerns the different forms that big data can take. Big data 
comes from many sources (such as from customers, competitors, 
suppliers and social media). This variety of sources means that big data 
is unstructured, can take many forms and means that it needs to be 
analysed carefully before it becomes useful. It also makes it harder to 
store this data in traditional databases. 
Veracity 
Veracity concerns the trustworthiness or accuracy of big data. Despite 
an organisation’s best efforts, data sets will contain inaccuracies, bias, 
anomalies and 'noise'. Therefore as much as possible needs to be done 
to clean up the data before it can be trusted as accurate. 
Capturing and managing big data is one thing, but to be of use to the organisation the data needs to 
have meaning. The process of 
data analytics
creates value for the organisation by drawing meaning 
from the data that the organisation has. This process typically involves assembling the data using fields 
within the source data itself. The data is then be filtered, sorted, highlighted and presented visually 
using, typically, bar charts and pie charts.