Key term
CCEA A-Level Digital Technology 2650
Systems Analysis and Development Approaches
Topic overviewThe software crisis and the need for systems developmentUser needs, time and costRoles in a systems development teamThe purpose of analysisFact-finding techniquesFunctional and non-functional requirementsData flow diagramsThe waterfall modelRapid application development and AgileResources, constraints and risks in a software projectProject management, Gantt charts and critical path analysisVersion management
Design, Development and Testing
Topic overviewThe purpose of systems designStoryboarding the user interfacePrototyping the interface and the data modelThe development stage: turning a design into working codeWhy testing runs throughout developmentLevels of testing: unit and integrationSystem testingAcceptance testingAlpha and beta testingThe purpose and components of a test planTypes of test data
Implementation and System Security
Topic overviewThe purpose of system implementationDirect and parallel changeoverPilot and phased changeoverUser documentationTechnical documentationData conversionThe purpose of system maintenanceCorrective, adaptive and perfective maintenanceArchiving dataBackup and recoveryFull, differential and incremental backupsDisaster recovery plans
Programming
Topic overviewThe purpose of a computer programThe integrated development environmentTranslation: compilers, interpreters and assemblersThe stages of compilation and linkingAlgorithms, pseudocode and syntaxVariables, constants and data typesSequence and selectionIteration: count-controlled and condition-controlled loopsFlowcharts and algorithm representationObjects, classes and methodsInheritance and evaluating the object-oriented approach
Data, Information and Data Representation
Topic overviewBits, bytes and units of storageHow many values a given number of bits can holdConverting decimal to binaryConverting binary to decimalTwo's complement and negative numbersCharacter sets: ASCII and UnicodeData, information and knowledgeFactors affecting the quality of informationValidation: range, type, length and presence checksValidation: format checks and lookup checksCheck digits and the Modulus 11 methodBatch totals, verification and the limits of checking
Computer Architecture and Processing Systems
Topic overviewThe processor, the clock and the registersThe fetch-execute cycleBuses, input and output controllers and portsMain memory: RAM, ROM and addressingCache memory and the memory hierarchyFactors that affect processing speedThe need for secondary storageMagnetic, optical and flash storage mediaChoosing secondary storage for common applicationsBatch, real-time and transaction processingAutomatic teller machines and point of sale terminalsSmartphones: input, output and processing
System Software, Application Software and the User Interface
Topic overviewUser interfaces: WIMP, command line and forms dialogueChoosing and evaluating a user interfaceInputting text, sound and videoThe purpose of an operating systemHow an operating system manages memory and processesTypes of operating systemUtility programsThe need for data compression, lossless and lossyZipping and archive filesCommon data file formatsApplication software: generic and special purposeObtaining and delivering software
Web Technology and Multimedia
Topic overviewThe internet, the World Wide Web and web standardsURLs, HTTP and the request-response cycleDomain names, DNS and IP addressesWeb browsers, search engines, cache and cookiesWeb servers, hosting, ISPs and file transferIntranets and how an organisation uses oneCreating web pages with HTMLHTML tags for text, lists, images and linksStyling pages with CSSMultimedia assets in a web pageClient-side and server-side processingSecurity over the internet: encryption, HTTPS and certificates
Networks
Topic overviewNetwork scope: LAN, MAN and WANNetwork hardware and connection devicesIP addresses and MAC addressesPeer-to-peer and server-based networksBus, star and ring topologiesThe need for communication protocolsThe OSI seven-layer modelTCP/IP, Ethernet and media access methodsWi-Fi, Bluetooth, VoIP and RFIDBandwidth and broadbandTransmission media: metal cable, fibre optic and wirelessDetecting and correcting transmission errors
Databases
Topic overviewThe relational database and its main featuresLogical and physical data modelsEntities, attributes and keysEntity-relationship modellingNormalisation to third normal formThe data dictionaryStructured Query Language: creating and changing dataStructured Query Language: retrieving dataQuery By Example and alternatives to SQLDatabase security, integrity and recovery
Artificial Intelligence, Expert Systems and Robotics
Topic overviewWhat artificial intelligence meansThe Turing test and machine intelligenceNeural network modellingThe structure of an expert systemThe knowledge base and the inference engineShells, heuristics, fuzzy logic and the knowledge engineerExpert systems in medicine, fault diagnosis and insuranceNatural language processingVoice recognition technologyEvaluating natural language and voice recognition systemsThe technology of roboticsRobotics in commercial situations
Mobile Technology, Data Mining and Cloud Computing
Topic overviewCells, masts and frequency reuseHandoff between cellsThe base station controller, the mobile switching centre and the PSTNWhat data mining isGathering and storing data for miningProcessing and analysing large volumes of dataBig data in health, finance and retailData mining and the privacy of the individualWhat cloud computing isVirtualisation, hosted instances, hosted solutions and clusteringCloud services: storage, email, software and backupEvaluating cloud computing for business
Individual, Social and Legal Considerations
Topic overviewThe Data Protection Act 2018 and the UK GDPRThe data protection principles and the rights of the data subjectThe Copyright, Designs and Patents Act 1988The Computer Misuse Act 1990Data protection duties of an organisationHow the legislation affects employees and the publicThe ethics of automated decision makingOnline censorshipMonitoring of personal behaviourThe ethics of artificial intelligence and of personal information
The Development Project: Analysis and Design
Topic overviewScheduling the project with a Gantt chartInternal and external constraints on the solutionDetailing user requirements as inputs, processes and outputsPrioritising requirements as essential and non-essentialData flow diagrams at level 0 and level 1Specifying hardware and software requirementsThe overall system designProcess descriptions and algorithmsUser interface design and validationData modelling and normalisation for the solutionDesigning the queries and reportsDeveloping a comprehensive test plan
The Development Project: Build, Testing and Evaluation
Topic overviewChoosing software to develop the solutionBuilding the solutionTest data and the types of testingCarrying out and recording the testingDocumenting a strategy for system implementationEvaluating the solution against the user requirementsIdentifying extensions to the systemThe electronic user guideBringing the system into use and supporting itDocumentation for the completed system
Mobile Technology, Data Mining and Cloud Computing
Data mining and the privacy of the individual
- 3 things to know
- A2 Unit 1
Overview
How aggregation turns harmless data into sensitive data, sensitive fact that mining can infer without being told it and function creep.
What you need to know
Answer each one before you reveal it.
Your recallNot started
Key term
How does data mining allow an organisation to know more about a person than that person told it?
Key term
What is function creep?
Questions from this subtopic
Each one with the model answer underneath.
- 1
How does data mining allow an organisation to know more about a person than that person told it?
Model answer
Data mining combines records collected for many separate purposes into a single detailed profile, so an organisation ends up holding a picture of an individual that the individual never knowingly supplied.
- 2
Explain how aggregation turns harmless data into sensitive data.
Model answer
Individually trivial items become sensitive once combined, because a home address, a pattern of journeys and a list of purchases together reveal a person's daily routine and circumstances.
- 3
Give an example of a sensitive fact that mining can infer without being told it.
Model answer
A change in the pattern of a customer's purchases can lead a retailer to infer a pregnancy or a health condition that the customer has disclosed to nobody, and the inference is then acted on as though it were established fact.
- 4
What is re-identification, and why does it threaten privacy?
Model answer
Re-identification is working out who a record belongs to after names have been removed, achieved by matching remaining fields such as postcode, date of birth and sex against another data set that does carry names.
- 5
What is function creep?
Model answer
Function creep is the gradual use of data for purposes beyond the one it was collected for, so a record captured to deliver an order is later mined to decide what price that customer is shown.
- 6
Why are individuals often unaware of how much data is held about them?
Model answer
Much of the data mined is generated as a by-product of ordinary activity such as browsing, paying or carrying a phone, so it accumulates without any deliberate act of disclosure by the individual.
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