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Evaluating data-driven applications and solutions - Coggle Diagram
Evaluating data-driven applications and solutions
The explosion in data
big data
successful development of networks and the internet
Companies such as amazon web services and Microsoft offer data storage
Making storage costs extremely low
Data driven companies such as google, Microsoft, apple, Facebook build vast arrays of computing and data storage
Offer services such as online advertising
Evolving data security impacts
Data no longer collected just from input
Can track GPS
Allowed for turn by turn directions and other helpful tools
organizations can steal data
Information as a commodity
User information can be shared to help support an individual when in a database
Australian Privacy Policy was developed to support the ethical use of data
Consumer profiles can be sold and bought
Information used to gather wants and needs about potential customers
Information social evolution
Australian card, 1980s
Introduced to reduce issues such as tax evasion and illegal immigration
Interconnected database made up of several government databses
Used to identify fraudulent Medicare usage
Provided to all citizens
Required when preforming any identity-specific actions
Turned down due too privacy concerns
MyGov website, 2010s
Online authentication portal
Managed by the department of human services
Uses several 'challenges' before granting access
includes two-step verification
Used to increase online accessibility of personal information
The verdict
Has the new system been an improvement, or is it like the Australian card
Governments have collected info for years
Retention and disposal of data
Organizations require systems to deal with retention and disposal of data
Disposal of data no-longer required is demanded by law
Retention of important data is required by law
Metadata is he information surrounding the content of communications via voice and data
de-identification of organisational data
Companies trying to safely provided more uses for data
Encourages open access to data for the good of all
Review how the Australian privacy principles have been taken into account
Document a data dictionary to help end users to use the datasets
evaluating data-driven solutions
Evaluating while exploring data-driven problems and solutions
Enables us to gather ideas and information from a range of sources
Important to mind map and articulate concepts, ideas, issues, requirements and investigations
informally evaluating the sustainability of technology approaches
used to develop function and non-function requirements
Evaluating while developing solutions
during development stages
structured data
visualises different approaches
Evaluating while generating solutions
solution components are generated and assembled
testing is helpful
Evaluating Solutions
refer back to criteria
determine whether aims have been met