Candidates should be able to:
1.1 Data, information and knowledge
• define data, clearly identifying that data has no meaning
• define information and show how data can become information through context and meaning
• define knowledge and understand that information becomes knowledge when human experience is applied
1.2 Sources of data
• define static data and give an example
• define dynamic data and give an example
• compare the use of static information sources with dynamic information sources
• define direct and indirect data source
• understand the advantages and disadvantages of gathering data from direct and indirect data sources
1.3 Quality of information
• understand how accuracy, relevance, age, level of detail and completeness of the information can affect its quality
1.4 Coding, encoding and encrypting data
• describe the coding of data (including: M for male, F for female) and more intricate codes (including:
clothing type, sizes and colour of garment)
• discuss the advantages and disadvantages of the coding of data
• evaluate the need for encoding data and analyse the different methods that can be used to encode data (including: codecs)
• define encryption and describe different methods of encryption (including: symmetric, asymmetric, public key, private key)
• evaluate the need for encryption and how it can be used to protect data such as on a hard disk, email or in HTTPS websites
• discuss encryption protocols (including: the purpose of Secure Socket Layer (SSL)/Transport Layer Security (TLS) and the use of SSL/TLS in client server communication)
1.5 Checking the accuracy of data
• define validation and analyse a range of validation methods (including: presence check, range check, type check, length check, format check and check digit, lookup check, consistency check, limit check)
• define verification and analyse verification methods (including: visual checking and double data entry)
• explain the need for both validation and verification
• define proof reading