Strategies for information Flashcards
The benefits of a proposed information system
The benefits of a proposed information system should be evaluated against the cost. Several factors need to be considered. These include the following:
Increased revenue
Improved marketing and use of data analytics can help organisations achieve a
competitive advantage.
Cost reduction
Automated production, computer aided manufacturing and improved stock
control may improve profitability.
Enhanced service
Computerised systems may improve reliability and CRM systems can help to
manage customer relationships.
Improved decision-making
Accurate and up-to-date information can aid forecasting and scenario planning.
Development and implementation of a new information system
Stages to follow when developing and implementation a new information system
Analysis
Identify the needs of the new system
Design
Design a system that needs those needs
Programming
Outline specifications to programmers
Testing
Ensure that requirements have been met
Conversion
Existing data is migrated to the system
Implementation
User training and on-going maintenance
Digital disruption
Digital disruption refers to the rapid change that is happening in many industries as
organisations move to digital transformation. This is through the use of technological
advances to challenge the status quo and create value in new ways
Digital technology has been used to disrupt many industries, including:
Transport e.g. Uber taking on traditional taxi firms
Accommodation e.g. Airbnb competing against hotels
Advertising e.g. social media influencers competing with traditional advertising
agencies
Data analytics
Data analytics is the process of collecting, organising and analysing
large sets of data to discover patterns and other information which an
organisation can use for future decisions.
Collection of data
Organisations have access to greater
quantities of data available from a number
of internal and external sources.
Organisation of data
Once the data has been captured it needs
to be organised and stored for future use,
often using data warehousing facilities.
Analysis of data
Data mining software uses statistical
algorithms to discover correlations and
patterns to create useful information.
Big Data
Big Data is a term that describes large volumes of data that inundate a
business on a day-to-day basis
The key features of Big Data are described as the 4Vs:
Volume
Considers the
amount of data fed
into the organisation
Does the organisation have the resources
available to store and manage this data?
Or does it have the financial resources
required to invest in or upgrade IT/IS?
Velocity
Considers the speed
that data is fed into
the organisation
Are systems able to capture and process
‘real time’ data?
Does the organisation have the skills to
provide timely analysis of this data?
Variety
Considers the
various formats of
data received
Are systems compatible and capable of
accepting various forms of data?
Legally, is the data owned by the
organisation or by the third party?
Veracity
Considers the
reliability of the data
being received
Can the organisation challenge data
received from third parties?
Is the data received fully representative of
the whole data population?
Barriers and limitations of Big Data
Data overload
Ability to verify the data
Representative data
Shortage of talent to analyse the data
Fear of cyber attack
Legal and regulatory compliance
Cognitive technologies (also known as intelligent systems)
Computer-based systems that represent, reason about and interpret
data. In doing so they learn about the structure of the data and analyse
it to extract patterns and meaning.
They then derive new information and identify strategies and
behaviours built upon the results of their analysis.
Artificial intelligence
Increasing use of computers to perform tasks thought to require human
intelligence such as learning and reasoning, including:
– Medical diagnosis through interpretation of medical images
– Home assistants learn our language and habits to better predict and
understand our requirements.
Machine learning
Is a subset of AI that applies algorithms or other techniques to data to give
computers the ability to learn without being explicitly programmed to do so.
Performance can be improved with experience of repeating processes.
– This can reduce costs, improve efficiency and reduce dependence on
human intervention
– For example: computer speech recognition to translate audio into text
Automation
The creation of technology and its application to control and monitor activities
without human interference. Cognitive technologies and artificial
intelligence facilitate the process of automation.
– Benefits include more productivity, accuracy, consistency and availability
– Challenges include the investment required, lack of operating skills and
potential redundancies.
Internet of things
This describes the inter-connection via the internet of computing devices embedded
in every-day objects, enabling them to send and receive data.
This has benefits for individuals (e.g. a heating system that responds to the changes
in weather) and also for businesses.
Digital assets
A digital asset is any text or data file that is formatted into a binary
source which includes the right to use it; digital files that do not carry
this right are not considered digital assets.
A business needs to protect and manage their digital assets in the same way they
would manage their tangible assets. If a logo was wrongly altered and then used
within an advertisement it could damage the reputation of the company.
Businesses use methods such as encoding, encryption and watermarks to protect
digital assets
Two common types of digital asset are:
Media assets (images and multimedia)
Textual content (documents, PDF files)