Core B - topics and key ideas

 Core B – topics and key ideas 

 

What does core B consist of? 

Core B consists of the remaining 4 components in digital infrastructure: 

• Digital support services pathway 

• Tools and testing 

• Security and legislation 

• Data and digital analysis 

Each component has lots of different aspects and ideas that need to be memorised for the test. 

Question structure 

• 1 mark – usually a “state” or “identify” question. You should only write one or a few words, do not describe unless it tells you. Spend 1 minute. 

• 2 marks – mainly “describe” questions. You should state what you are speaking about and describe it, 2 sentences maximum. Spend 2 minutes. 

• 3 marks – an extension of the 2-mark questions, however you should explain in greater detail. Try to reread the question when writing to make sure you are answering it correctly. Spend 3 minutes. 

• 4 marks – usually an “explain 2 ways” question. Just think of it as 2x 2-mark questions together. Try to link or compare in some way as well to solidify the 4 marks. Spend 5 minutes. 

• 6 marks – could either be an “evaluate” or “describe 3” question. In the case of evaluating, try to consider multiple points (2 or 3) and make conclusions about them. In a “describe 3” situation treat it as 3x 2-mark questions. Spend 8 minutes. 

• 12 marks – There are only 2x 12-mark questions in Core A. This question requires in depth analysis and judgements. Try to start with an introduction paragraph, only one or 2 sentences explaining the situation. Then create your 3 main points you want to analyse. They must be relevant to the question its asking or the scenario it has given. Try and read into the scenario, they often give you points already which you can use. After explaining each point in depth, you should create a conclusion where you weigh up all the points you have talked about. Make sure to reference the question at the end for maximum marks. Also note there are 3 additional marks available for QWC (quality of written content) so use correct grammar and make sure it all makes sense together. Spend 15 minutes. 

Importance of key words 

The examiners are looking for usage of keywords in the answers you give. For example, if you write about something try to mention technical keywords that relate to the scenario they give you. Sometimes thinking of keywords before answering a question can help. Also, keywords can be included in the question itself which you should reference in your answer. More keywords = more marks. 

 

Section A: Digital support services pathway 

 

Support lines 

• 1st line support – The front of the support line which usually has a broad understanding of the product. 

• 2nd line support – Deals with problems that are too technical or time consuming for 1st line support. They are usually more specialist in the product. 

• 3rd line support – Highly technical support used for in-depth fault analysis and fixing. 

 

Careers in the digital support sector 

• Desktop support 

• Network support 

• Server administrator 

• Network administrator 

• Network engineer 

• Systems engineer 

• Network architect 

• Solutions architect 

• Consulting engineer 

 

Communication formats 

• Telecommunication - Large data transmission over large distances by electronic means. 

• Email – An online message format including attachments and text. 

• Face-to-face conversation – Physical conversations. 

• Presentations – Presenting information in front of a group or individual. 

 

Fault analysis tools 

• Activity/error logs – A record of all interactions and events within a network system. 

• System alerts – Flags when the system is not meeting set parameters. 

• Live traces – Identification of network activity in real-time. 

• Dashboards – A visual representation of a system including KPIs and condition. 

 

Section B: Tools and testing 

 

Presentation tools 

• Slide/page presentation software – Used to create and share informational pages or slides. 

• Digital infographics – A visual representation of information. 

• Graph – A visual representation of the mathematical relationship between 2 data sets. 

• Dashboards – A virtual display of complex data and metrics. 

 

Project management methodologies 

• Agile – An iterative approach that manages a project throughout its lifecycle. 

• Scrum – A flexible and adaptable framework that uses meetings and reviews to track progress in an iterative manner. 

• Kanban – A simple, “just in time” approach where tasks are completed only when required. 

• Lean – Used to minimise waste and maximise the project’s value. 

• Sprints – A regular repeated work cycle in iterative project management methods. 

• Waterfall – A linear approach to project management where previous phases must be completed before progression. 

• Spiral – A methodology which focuses on risk analysis and mitigation. 

• Rapid application management (RAD) - An agile approach which minimises planning and focuses on application development. 

 

Project management tools 

• Gantt charts – Fast graphical representation of all the tasks required to be completed in a project. 

• Flowchart – A visual display made of geometric shapes which shows tasks, workflows, dependencies and processes. 

• Stakeholder power-interest matrix – Used to analyse a stakeholder’s power and interest in a project. 

• Budget sheet – A combination of all costs in a project which allows for a budget to be estimated. 

 

Evaluation tools 

• Quantitative – Used to measure a quantity of something. 

• Qualitative – Tools used to measure qualities and features. 

• Marketing analytics – Analysis into the market in which the product is being released to or targeting. 

• Strengths, opportunities, weaknesses and threats (SWOT) - An analysis tool used to identify components and help with estimating feasibility and ROI. 

 

Data mining 

• Tracking patterns – Recognising patterns in the data. 

• Classification – Categorising the data based off its attributes. 

• Association – Looking for correlations between attributes. 

• Anomaly detection – Establishing data outliers and anomalous results. 

• Clustering – Grouping data based on their similarity. 

• Prediction – Modelling data to make future predictions. 

 

Communication tools 

• Intranet – Private, secure networks used to share information internally in an organisation. 

• Shared workspaces – Workstations that are accessible virtually or physically which promote collaboration. 

• Shared documents – Documents which are shared with other people. 

• Discussion threads – Text channels allowing people to share ideas and collaborate. 

• Online shared storage – Storing data with a third-party provider over the internet. 

• Mark-up – Comments and tracked changes within a document. 

• Video conferencing – A method of visual communication over the internet using cameras and microphones. 

 

Testing methods 

• Functionality testing – A confirmation of the functionality of digital components. 

• Usability testing – Testing a digital technology’s usability and end user satisfaction. 

• Compatibility testing – A type of test that confirms if computer software/hardware can run alongside different digital environments. 

• Accessibility testing – Testing for users who have accessibility requirements. 

• End user satisfaction testing – Where end user satisfaction is tested to confirm whether they have a positive experience or not. 

• Fault finding and debugging – Locating and fixing errors and problems. 

• Impact assessment – Analysing the implications of proposed digital implementations. 

• Efficiency of individual components – Testing the performance of a single component. 

• Review accuracy of data – Reviewing how accurate and the quality of data held. 

• Ensuring desired outcomes – Comparing actual outcomes with desired outcomes. 

• Root cause analysis (RCA) - A method to get the root of a problem solved. 

• Five whys – Asking 5 why questions for root cause analysis. 

• Stress testing – Replicating real world loads to test how the system handles it. 

• Load testing – Using high traffic loads to test the system under intense pressure. 

• Penetration testing – Used to determine and fix vulnerabilities in a system. 

• Black box testing – A test conducted by comparing outputs to expected results. 

• White box testing – A test conducted where the tester is given information about the system first to test functionality and security in-depth. 

 

Section C: Security and legislation 

Confidential data 

• Human resources (HR) - Data around employee salaries, perks and medical information. 

• Commercially sensitive data – Information from a business that should be kept classified such as sales data, trade secrets and profit margins. 

• Client and customer details – Details about customers and clients such as addresses, phone numbers and payment information. 

 

CIA triad 

• Confidentiality – Ensuring that systems holding data are protected from unauthorised viewing. 

• Integrity – Data is protected from unauthorised changes or tampering. 

• Availability – Only authorised users have access to the data. 

 

Technical threats 

• Botnets – Malware which is used to turn computers into “zombie machines” allowing hackers to remotely control them as a large group of bots. 

• Denial-of-service (DoS) - When a large volume of illegitimate packets is sent to a digital system from a single place, denying legitimate packets to be transmitted. 

• Distributed denial-of-service (DDoS) - When a large volume of illegitimate packets is sent to a digital system from multiple places, denying legitimate packets to be transmitted. 

• Cross site scripting (XSS) - Inserting malicious code into a web application to be executed on victim’s machines. 

• Password cracking – Used by hackers to break encrypted password hashes allowing them entry to accounts and systems. 

• SQL injection – Exploiting weak SQL queries and attacking databases to leak information or allow unauthorised access to the hacker. 

• Malware – Malicious programs installed by hackers to spy on or disrupt victim’s machines. 

• Malicious spam – Junk emails or other communication methods used to trick users into giving away personal details. 

• Buffer overflow – When data overruns the buffer boundary and injecting malicious code into other buffers. 

 

Non-technical threats 

• Human error – Humans accidentally leaking or losing data. 

• Malicious employees – Rogue employees who want to harm the systems and steal data for personal gain. 

• Disguised criminals – Physical threat actors who gain entry to buildings using social engineering techniques. 

• Natural disasters – Natural disasters like earthquakes could make data inaccessible for cloud users without backups. 

 

Technical vulnerabilities 

• Weak or outdated encryption – When encryption methods are not sufficient to protect the data. 

• Out-of-date software – When software is not updated with the latest security patches, making it vulnerable. 

• Weak passwords – Passwords that can be easily guessed by hackers. 

• Missing authentication – When users do not have to be authenticated to access a system. 

• Zero-day bugs – Bugs that have been found and are being exploited by bad actors. 

 

Non-technical vulnerabilities 

• Employees – Humans are the weakest link in any digital system and can be targeted by hackers. 

• Poor data/cyber hygiene – When data is not kept up to date. 

• Physical access controls – Physical locks and boundaries to protect hardware from unauthorised access. 

 

Cyber risk mitigation 

• NCSC Cyber Essentials – A guidance developed for businesses to follow so they are updated on cyber security and the need to protect data. 

• Anti-malware – A program used to recognise and destroy malicious programs which have infected a system. 

• Firewall – A security device that examines and controls data packets trying to enter the network from external sources like the internet. 

• Intrusion detection/prevention systems – Programs designed to detect and prevent security compromissions in a network. 

• Encryption – A method of disguising data during transmission or storage so that hackers can't intercept and read it without the correct key. 

• Access controls – Denying and allowing access to certain staff. 

• Multi factor authentication – Authenticating users multiple times to increase security. 

• Staff training – Educating employees on cyber threats to increase awareness and knowledge. 

• Backups – Backing up data so that it can be restored if lost. 

• Air gapping – Creating a digital system that is physically isolated from any potentially dangerous network. 

• Honeypot – A virtual system used to imitate a real system and attract hackers where they can be detected. 

• Virtual private networks (VPNs) - Secure connections from one network to another over the internet. 

 

UK legislations 

• Health and safety at work act 1974 

• Work at height regulations 2005 

• Manual handling operations regulations 1992 

• Management of health and safety at work regulations 1999 

• Health and safety (display screen equipment) regulation 1992 

• Investigatory powers act 2016 

• Freedom of information act 2000 

• Computer misuse act 1990 

• Digital economy act 2017 

• Public sector bodies (websites and mobile applications) (No. 2) accessibility regulations 2018 

• Copyright, designs and patents act 1988 

• Waste electrical and electronic equipment directive 2012 

• Human rights act 1998 

• General data protection regulations 

 

International regulations 

• European convention on human rights 

• Electronic communications privacy act 1986 – USA 

• Controlling the assault of non-solicited pornography and marketing act 2003 – USA 

 

Section D: Data and digital analysis 

Data types 

• Numeric – Data represented as number values. 

• Text – Data represented using characters and words. 

• Media – Data represented as visual or audio formats. 

• Geospatial – Data represented as physical locations. 

• Temporal – Data represented as time values. 

• Logical – Two states or Boolean choices like 1 or 0. 

 

Data storage 

• Internal database – An organised collection of data stored on an internal server. 

• File structures – Data organisation within files and folders. 

• Hard drives – Data can be stored on physical storage devices. 

• Network attached storage (NAS) - A storage device that is connected to a network. 

• Storage area networks (SAN) - A network of interconnected storage devices. 

• Cloud storage – Data stored as a service (Daas) over the internet. 

• Object storage – When files are broken into pieces and spread out among storage devices. 

• Block storage – When a file is split into blocks and stored separately. 

 

Applications of data 

• Input – Collection of raw data from source. 

• Storage – Saving the data so it can be used again. 

• Processing – Converting the data into a meaningful output. 

• Output – When the data is sent to the relevant people. 

• Feedback loop – An output that is returned to the senior manager. 

 

Data modelling 

• Data model – Logical relationships and data flow between different data elements. 

• Conceptual data model – Defines what the system contains. 

• Logical data model – How the system should be implemented. 

• Physical data model – Describes how the system is implemented using a specific DBMS. 

• Hierarchical database model – Shows the data model as a tree structure. 

• Relational model – Shows databases as a collection of relationships. 

• Data dictionary – Contains information about the data that will be stored in a database. 

• Entity relationship diagrams (ERD) - Used during the creation of data models and to design relational databases. 

• Data flow diagrams (DFDs) - Models of how data and information flow through a system. 

 

Data entry and maintenance 

• Data entry – When data enters a digital system. 

• Data verification – Data is verified or cross checked to ensure no data errors occur. 

• Data validation – A check run by the digital system when data entry occurs. 

• Privacy – Data should be kept private and hidden from unauthorised viewing. 

• User – A person who can make changes to the data. 

• Digital system administrator – An administrator over who can control the data. 

 

Data formats 

• File-based – When data is held in a single file. 

• Directory-based – When data is held across many files. 

• Relational database system – When data is connected through relationships. 

 

Visualisation and presentation 

• Reports – Data being formatted and overviewed in a report format. 

• Digital slides – Used in presentations to convey information. 

• Webinars – Video conferences where data is shared. 

• Extended reality – An immersive presentation of data using VR, AR and MR. 

• Video and sounds – Using media formats to present and release data. 

• Animation – Visually animated images which can present data. 

• Graphs and charts – A visual representation of data and data comparisons. 

• Dashboard – GUI based overview of data for one system. 

• Data table – When data is presented in the same category. 

• Infographic – A visual representation of information or data. 

• Maps – Used to display data compared to a geographical map. 

 

Algorithms 

• Algorithm – A set of instructions used to solve a problem. 

• Decomposition – Breaking the problem down into smaller, more manageable stages. 

• Pattern recognition – When a problem has been decomposed, and patterns can be identified in the steps. 

• Abstraction – Removing or filtering characteristics that are not needed to focus on the main goal. 

• Actions – When algorithms are correctly solved, and the correct output is produced. 

• Computational thinking – An umbrella term for decomposition, pattern recognition, abstraction and actions. 

• Iteration – When algorithms carry out tasks repeatedly until a certain condition is met. 

 

Tools for problem solving and algorithm design 

• Decomposition diagram – Shows tasks in the simplest form and how they link together. 

• Pseudocode – An informal programming language which is more human-readable and understandable. 

• Flowchart – A graphical representation of the steps within an algorithm.