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ICAP CAF CAF-3: Data, Systems and Risks Syllabus

The CAF-3: Data, Systems and Risks syllabus for ICAP CAF in full: 6 chapters and 18 topics, every one listed below, plus 50 CAF-3: Data, Systems and Risks flashcards with answers.

6Chapters
18Topics
50Flashcards

CAF-3: Data, Systems and Risks syllabus: all 6 chapters

Expand any chapter to see its topics and sub-topics.

  1. Data Fundamentals

    2 topics
    • Types, sources and collection of data
    • Data governance, classification and management
  2. Data Analytics and Big Data

    2 topics
    • Stages of data analytics
    • Big Data characteristics and applications
  3. Database Management

    3 topics
    • Normalization and data warehousing
    • ETL (Extract, Transform, Load)
    • Database management systems
  4. IT Systems Architecture

    4 topics
    • Hardware, software and networks
    • ICT for organizational efficiency
    • Adequacy of systems, processes and controls
    • ERP systems and cloud computing
  5. IT Governance and Emerging Technologies

    3 topics
    • IT governance frameworks and ROI
    • Emerging technologies
    • Digital disruption and the accountancy profession
  6. Risks and Controls

    4 topics
    • Risks in physical and digital IT environments
    • Cyber and information security risks
    • IT general controls
    • Frameworks and regulations

ICAP CAF CAF-3: Data, Systems and Risks flashcards — 50 questions with answers

  1. What is the difference between qualitative and quantitative data?

    Quantitative data is numerical and measurable (e.g. sales figures, quantities). Qualitative data is descriptive/non-numerical, describing qualities or characteristics (e.g. opinions, colours, customer feedback).

  2. Distinguish between primary and secondary data sources.

    Primary data is collected first-hand by the organisation for a specific purpose (e.g. surveys, interviews, observations). Secondary data already exists, collected by someone else for another purpose (e.g. published reports, government statistics, databases).

  3. What is the difference between internal and external data sources?

    Internal data is generated within the organisation (accounting records, HR data, production logs). External data comes from outside (market reports, competitor data, economic statistics, social media).

  4. What is the difference between structured, unstructured and semi-structured data?

    Structured data is organised in a defined format such as rows and columns in a database. Unstructured data has no predefined model (emails, images, videos, text). Semi-structured data has some organisational tags or markers but is not in a strict table format (XML, JSON).

  5. List common methods of data collection.

    Surveys/questionnaires, interviews, observation, focus groups, experiments, document/record review, web scraping, sensors/IoT, and automated transaction capture.

  6. What is data governance?

    The overall framework of policies, processes, roles, standards and controls that ensure data is accurate, available, consistent, secure and used appropriately across the organisation.

  7. Define a data owner and a data steward.

    A data owner is accountable for a data set, its quality, classification and access decisions (usually a senior manager). A data steward is responsible for the day-to-day management, quality and proper use of the data.

  8. What are the four common levels of data classification?

    Public, Internal (or internal use only), Confidential, and Restricted/Highly Confidential (Secret). Classification determines the level of protection and access controls applied.

  9. List the key dimensions of data quality.

    Accuracy, Completeness, Consistency, Timeliness, Validity, Uniqueness (no duplication), and Reliability/Integrity.

  10. What is the data life cycle?

    The stages data passes through: Creation/capture, Storage, Usage/processing, Sharing, Archiving, and Destruction/disposal.

  11. What are the typical stages of data analytics?

    1) Define objective/question, 2) Data collection, 3) Data cleaning/preparation, 4) Data analysis, 5) Interpretation, 6) Visualisation/communication, and 7) Action/decision-making.

  12. Distinguish descriptive, diagnostic, predictive and prescriptive analytics.

    Descriptive: what happened. Diagnostic: why it happened. Predictive: what is likely to happen. Prescriptive: what should be done about it (recommends actions).

  13. What is data cleaning (data cleansing)?

    The process of detecting and correcting (or removing) inaccurate, incomplete, duplicated or improperly formatted data to improve data quality before analysis.

  14. What are the 'V' characteristics of Big Data?

    Volume (huge amounts), Velocity (high speed of generation/processing), Variety (different types/formats), Veracity (trustworthiness/quality), and Value (usefulness).

  15. Give examples of Big Data applications in business.

    Customer behaviour analysis and targeted marketing, fraud detection, risk management, predictive maintenance, supply chain optimisation, credit scoring, and personalised recommendations.

  16. What is data normalization in databases?

    The process of organising data in a database to reduce redundancy and improve data integrity by dividing data into related tables and defining relationships between them.

  17. What does First Normal Form (1NF) require?

    That each table cell contains a single (atomic) value and each record is unique, with no repeating groups or arrays in columns.

  18. What does Second Normal Form (2NF) require?

    The table must be in 1NF and all non-key attributes must be fully dependent on the entire primary key (no partial dependency on part of a composite key).

  19. What does Third Normal Form (3NF) require?

    The table must be in 2NF and have no transitive dependencies; non-key attributes must depend only on the primary key, not on other non-key attributes.

  20. What is a data warehouse?

    A central repository of integrated, subject-oriented, historical data drawn from multiple sources, structured and optimised for querying, reporting and analysis rather than transaction processing.

Show the other 30 CAF-3: Data, Systems and Risks flashcards
  1. How does a data warehouse differ from a data mart?

    A data warehouse is enterprise-wide, covering all subject areas. A data mart is a smaller, focused subset of a warehouse serving a specific department or business function.

  2. What is a data lake and how does it differ from a data warehouse?

    A data lake stores vast amounts of raw, unstructured and structured data in its native format until needed. A data warehouse stores cleaned, structured, processed data organised for specific analytical use.

  3. What does ETL stand for and what are its three stages?

    Extract, Transform, Load. Extract: pull data from source systems. Transform: clean, format, standardise and integrate the data. Load: write the prepared data into the target system (e.g. data warehouse).

  4. How does ELT differ from ETL?

    In ELT (Extract, Load, Transform) raw data is loaded into the target system first and transformed afterwards inside it, leveraging the target's processing power; in ETL transformation happens before loading.

  5. What is a Database Management System (DBMS)?

    Software that enables users to create, store, retrieve, update and manage data in a database, controlling access, integrity, security and concurrency.

  6. List key advantages of using a DBMS over file-based systems.

    Reduced data redundancy, improved data integrity and consistency, data sharing, better security and access control, data independence, backup/recovery, and concurrent multi-user access.

  7. What is a relational database?

    A database that stores data in tables (relations) made of rows and columns, where tables are linked through primary and foreign keys, and queried using SQL.

  8. Distinguish a primary key from a foreign key.

    A primary key uniquely identifies each record in a table. A foreign key is a field in one table that refers to the primary key of another table, establishing a relationship between them.

  9. What is the difference between hardware and software?

    Hardware is the physical components of a computer system (CPU, memory, storage, input/output devices). Software is the set of programs/instructions that tell the hardware what to do (system and application software).

  10. Distinguish system software from application software.

    System software manages the computer and its resources (operating systems, utilities, device drivers). Application software performs specific user tasks (word processors, accounting packages, spreadsheets).

  11. Distinguish a LAN from a WAN.

    A LAN (Local Area Network) connects devices within a small geographic area such as one building/office. A WAN (Wide Area Network) connects networks over large geographic areas, such as across cities or countries (the Internet is the largest WAN).

  12. What is a network topology? Name common types.

    The physical or logical arrangement of devices in a network. Common types: Bus, Star, Ring, Mesh, and Tree/Hybrid.

  13. How can ICT improve organisational efficiency?

    By automating routine tasks, speeding processing, reducing errors, improving communication and collaboration, enabling real-time information, reducing costs, supporting better decision-making, and improving customer service.

  14. What factors determine the adequacy of systems, processes and controls?

    Whether they meet business objectives, ensure data accuracy and completeness, are reliable and secure, are cost-effective, comply with laws/standards, are scalable, and include adequate controls and audit trails.

  15. What is an ERP system?

    Enterprise Resource Planning: integrated software that manages and connects an organisation's core business processes (finance, HR, supply chain, manufacturing, sales) through a single shared database in real time.

  16. State two key benefits and two key risks of ERP systems.

    Benefits: integration of processes/data and improved real-time information and efficiency. Risks: high cost and complexity of implementation, and business disruption/dependence on a single system (single point of failure).

  17. What is cloud computing?

    The delivery of computing services (servers, storage, software, databases, networking) over the internet on demand, typically paid for on a usage basis rather than owning the infrastructure.

  18. Distinguish IaaS, PaaS and SaaS.

    IaaS (Infrastructure as a Service): rents fundamental computing resources (servers, storage). PaaS (Platform as a Service): provides a platform to develop and deploy applications. SaaS (Software as a Service): delivers ready-to-use applications over the internet.

  19. State two advantages and two disadvantages of cloud computing.

    Advantages: scalability/flexibility and lower upfront capital cost (pay-as-you-go). Disadvantages: dependence on internet/provider and data security/privacy and loss-of-control concerns.

  20. What is IT governance?

    The framework ensuring that IT investments support business objectives, deliver value, manage risks and resources effectively, and align IT strategy with organisational strategy, with clear accountability.

  21. Name two widely used IT governance/control frameworks.

    COBIT (Control Objectives for Information and Related Technologies) and ITIL (IT Infrastructure Library); ISO/IEC 27001 is also used for information security management.

  22. What is COBIT?

    A framework developed by ISACA for the governance and management of enterprise IT, providing control objectives, processes and metrics to align IT with business goals and manage IT risk.

  23. How is Return on Investment (ROI) calculated?

    ROI = (Net Benefit / Cost of Investment) x 100, where Net Benefit = Total benefits (or gains) minus the cost of the investment. It measures the gain relative to the cost of an IT investment.

  24. List examples of emerging technologies relevant to accountancy.

    Artificial Intelligence/Machine Learning, Blockchain, Robotic Process Automation (RPA), Internet of Things (IoT), Cloud computing, Big Data analytics, and 3D printing.

  25. What is blockchain?

    A distributed, decentralised digital ledger that records transactions across many computers in linked, cryptographically secured blocks so that records cannot be altered retrospectively without altering all subsequent blocks and network consensus.

  26. What is Robotic Process Automation (RPA)?

    Software 'bots' that automate repetitive, rule-based digital tasks (such as data entry, reconciliations and report generation) by mimicking human interactions with applications.

  27. What is digital disruption and how does it affect the accountancy profession?

    Digital disruption is the transformation of business caused by emerging digital technologies. For accountants it automates routine bookkeeping/compliance, shifts the role toward advisory, analytics and assurance over technology, and demands new digital skills.

  28. Distinguish physical and logical (digital) IT risks/threats.

    Physical threats relate to hardware/environment: theft, fire, flood, power failure, physical damage. Logical/digital threats relate to data and systems: hacking, malware, unauthorised access, data corruption, denial-of-service attacks.

  29. Define the CIA triad of information security.

    Confidentiality (data accessible only to authorised users), Integrity (data is accurate, complete and unaltered), and Availability (data and systems are accessible when needed).

  30. What are IT General Controls (ITGCs)? Give the main categories.

    Controls over the IT environment that support reliable application processing. Main categories: access security/logical access controls, change management, program development, and computer/IT operations (including backups).

ICAP CAF CAF-3: Data, Systems and Risks FAQ

What is in the ICAP CAF CAF-3: Data, Systems and Risks syllabus?

ICAP CAF CAF-3: Data, Systems and Risks is split into 6 chapters: Data Fundamentals, Data Analytics and Big Data, Database Management, IT Systems Architecture, IT Governance and Emerging Technologies and Risks and Controls. Together they contain 18 topics.

How many chapters are in ICAP CAF CAF-3: Data, Systems and Risks?

6 chapters, containing 18 topics. The largest chapter is IT Systems Architecture, with 4 topics.

Are there flashcards for ICAP CAF CAF-3: Data, Systems and Risks?

Yes — a 50-card CAF-3: Data, Systems and Risks deck, printed in full in the flashcards section of this page and available in the Examius app with spaced repetition. The free plan covers one exam of your choice, including its flashcards; Examius Pro, a one-time purchase, unlocks every other exam and deck.