5.1 The 4th Industrial Revolution & Key technologies driving the digital world Flashcards

1
Q

An industrial revolution can be generalised as

A

a rapid and major change in an economy, driven by a shift in the methods and types of work undertaken

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2
Q

The technological developments predicted to drive the 4th revolution are:

A
  • cloud computing
  • big data
  • data analytics
  • process automation
  • artificial intelligence
  • data visualisation
  • blockchain
  • internet of things
  • mobile technologies
  • 3D printing
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3
Q

The characteristics predicted to define the 4th revolution include:

A
  • Fusion - cyber and physical systems will continue to fuse becoming increasingly autonomous
  • Employment - robotics, automation and digitisation are predicted to fundamentally change many jobs and create redundancies
  • Artificial intelligence and machine learning - improved computing speed and optimised supply chains, enables products to be customised more easily and more cheaply
  • Machine led manufacturing - an accelerated shift from machines helping workers manufacture, to workers helping machines
  • Improved asset management - benefits to the natural world through more efficient use of natural assets, a shift to renewables, innovations in recycling, coupled with digitisation
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4
Q

Cloud computing is defined as the:

A
  • delivery of on demand computing resources over the internet, including everything from applications to data centres
  • users log into an account in order to access, manage and process files and software via remote servers hosted on the internet
  • replaces traditional method of owning and running software locally on computer
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5
Q

Two main types of cloud setups:

A
  • Public cloud - hosted by a third party company. Specialist companies sell their cloud computing services to anyone over the pubic internet who wishes to purchase them
  • Private cloud - IT services provided over a private infrastructure, typically for use by single org and usually managed internally.
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6
Q

Advantages of cloud computing:

A
  • Flexibility and scalability - allows simple and frequent upgrades giving access to the latest system developments which allows the org to evolve and adapt to new opportunities and practices
  • Cost efficient - Limited IT maintenance costs and reduced IT hardware costs means capital expenses and fixed costs become operating expenses and allows for pay as you go based on bus needs
  • Security - providers are specialists and the security and integrity of their systems will be a strategic priority with disaster recovery and backups built in
  • Flexible working - increase in remote working is supported and ability to access your desktop from anywhere
  • Environment - Less waste from disposal of obsolete technology and more efficient use of scarce resources
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7
Q

Disadvantages of cloud computing:

A
  • Organisational change - working methods and roles need to be modified and may lead to job losses
  • Contract management - the provider will be a significant supplier and which will mean new challenges and costs as the bus will need to manage this relationship, monitor performance and ensure contractual obligations are met
  • Security, privacy and compliance - providers are targets for malicious agents which can threaten the security of sensitive info, plus compliance with data regulations is largely in the hands of a third party
  • Reliance - reliability of provider is essential as they will be providing the info systems that are fundamental to the operation of a bus
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8
Q

Big data describes:

A

data sets that are so large and varied that they are beyond the capability of traditional data-processing

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9
Q

The key features of big data (4Vs):

A
  • Volume - considers the amount of data fed into the org
  • Velocity - considers the speed that data is fed into the org
  • Variety - considers the various formats of data received
  • Veracity - considers the reliability of the data received
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10
Q

Two main forms of big data:

A
  • Structured data - is deliberately produced and collected for a specific purpose and therefore has a clear and deliberate structure (eg: feedback data from people rating a product or service)
  • Unstructured data - is captured passively without a clear purpose, it’s format is highly variable and non-standard (eg: social media posts and likes)
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11
Q

The principal sources of the two forms of big data are classified as follows:

A
  • Human sourced data - billions of data points produced from social media, text messages, web browsing, emails, etc
  • Machine generated data - smart technologies and the internet of things is a growing source of data
  • Processed data - traditional data held on bus databases recording customers, transactions and company assets
  • Open data - Publicly available data from sources such as governments, public sector and national statistics agencies
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12
Q

Data analytics is the process of

A

is the process of collecting (from internal and external sources), organising (often in data warehousing facilities) and analysing large sets of data (big data) to discover patterns and other info which an org can use to inform future decisions (using statistical algorithms)

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13
Q

Benefits of effective data analytics:

A
  • Fresh insight and understanding - seeing underlying patterns can give insight in to how a bus operates and reveal issues they didn’t know about
  • Performance improvement - data processed and sorted into relevant management info can lead to significant operational gains and improved decision making and use of resources
  • Market segmentation and customisation - refining customer groups into ever more specific segments and understanding the wants and needs of those groups can lead to increased personalisation and customisation of products and services
  • Decision making - real time info that is relevant can lead to faster decisions and decisive advantage over competitors
  • Innovation - existing products can be improved by understanding what features and elements customers enjoy and use or can lead to development of new products
  • Risk management - the use of data can enhance all stages of the risk management process
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14
Q

Process automation is enabled by

A
  • technology and enables automation of complex bus processes.
  • This can be entire processes or elements of it
  • and is aimed at improving consistency, quality and speed while saving costs
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15
Q

Traditional process automation involves

A
  • a machine carrying out simple repetitive tasks, replacing jobs that would have been done by hand or in a semi-automated fashion
  • this type of automation is everywhere and has driven industrialisation by being able to produce ever higher volumes of products with fewer problems and less costs
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16
Q

Modern process automation:

A
  • Increasingly automation and process automation are focusing on complex bus areas previously thought to be beyond the limits of technology
  • process automation is becoming smarter and can make decisions using reasoning, language and learned behaviour
17
Q

Artificial intelligence (AI) is an area

A
  • of computer science that emphasises the creation of intelligent machines that work and react like human beings
  • a systems ability to correctly interpret external data, to learn from such data and to use those learnings to achieve specific goals and tasks through flexible adaptation
  • AI has algorithms that process data and can use it to make recommendations
18
Q

Some of the more advanced activities and skills AI can now master:

A
  • Voice recognition
  • Planning
  • Learning
  • Problem solving
19
Q

Machine learning is a subset of

A
  • AI where effectively AI computer code is built to mimic how the human brain works.
  • it uses probability based on past experiences through data, events and connections between events
  • the machine then applies this learning to a given situation to give a fact driven plausible outcome
  • if the conclusion turns out to be wrong this will add more experience and enhance it’s understanding further, so in future same mistake wont be repeated
20
Q

Summary:

A
  • Big data and the internet of things generate huge amounts of data
  • Data analytics transforms this into useful info that supports
  • artificial learning and machine learning
21
Q

Data visualisation allows

A

large volumes of complex data to be displayed in a visually appealing and accessible way that facilitates the understanding and use of the underlying data

22
Q

The most common use of data visualisation is

A

in creating a dashboard to display the key performance indicators of bus in live format, which allows immediate understanding of current performance and potentially prompts action to correct or amend performance accordingly

23
Q

An effective data visualisation tool should display these five features:

A
  • Decision making ability - results focused, should aid decision making
  • Effective infrastructure - the output is reliant on sufficient quantity and quality of data
  • Integration capability - with existing systems and the bus overall
  • Prompt understanding and insight of data - live data is vital, a delay can limit the usefulness of data or cause any insight to be useless
  • Real time collaboration - users must interact with each other and the data
24
Q

A blockchain has been described as a

A
  • decentralised, distributed and public digital ledger that is used to record transactions across many computers
  • this means record cannot be altered retroactively without the alteration of all subsequent blocks and the consensus of the network
  • simply it is a technology that allows people who do not know each other to trust a shared record of events
25
Q

Benefits of a blockchain:

A
  • Main benefit is security
  • Anything of value can be transferred
  • No need for an intermediary
  • Cyber security is an issue of traditional closed systems as modifications to data are carried out by one party
  • Blockchains provide an effective control mechanism aimed at addressing these cyber security risks
  • It has been described as a form of collective bookkeeping
26
Q

Key features of a blockchain:

A
  • transactions are recorded and maintained by a number of participants using a network which operates via the internet
  • when a transaction takes place the details are recorded by everyone, all participants must be in agreement before transaction is accepted
  • the process of verifying the transaction is done by computers, once all the computers verify the details the records on all participants in blockchain are updated (a single system can’t add blocks to chain)
  • when a new block is added it is linked to the previous block using a cryptographic hash generated from the contents of previous block. This ensures that the chain is never broken and that each clock is permanently recorded.
27
Q

Typical stages in a blockchain transaction:

A
  1. A transaction is required
  2. A block is created as a digital representation of the transaction
  3. The block is sent to every node in the network (distributed ledger)
  4. The nodes validate the authenticity of the transaction
  5. The nodes receive a reward for the proof of the work (ie. bitcoin)
  6. The completed authorised block is added to the chain
28
Q

The internet of things describes the

A
  • network of smart devices with inbuilt software and connectivity to the internet allowing them to constantly monitor and exchange data
29
Q

Mobile technologies are underpinned by:

A
  • Code-division multiple access (CDMA)
  • it has developed rapidly over the last decade and increased the capability of mobile technology
30
Q

3-D Printing is part of a process known as

A
  • additive manufacturing where an object is created layer by layer
  • it allows complex parts and components to be produced much cheaper, faster and in an entirely customisable manner
31
Q

Advantages of 3-D printing:

A
  • Speed
  • Cost effectiveness
  • Customisation
  • Less waste
  • Confidentiality