Learn Computing - F200: Fundamentals of Data Analytics

F200: Fundamentals of Data Analytics

1.1: Data, information and knowledge

Data, information and knowledge
Sources of data, information and knowledge
Interaction of data, information and knowledge
Data and information in society

1.2: Big data

1.3: Data and file formats

American Standard Code for Information Interchange (ASCII)
Audio file formats
Extensible Markup Language
JavaScript Object Notation (JSON)
Numeric and plain text data formats

1.4: Data and classifications

Data types
Classifications of data

2.1: Data lifecycle management (DLM) and the data analytics pipeline

The five phases of the data lifecycle
Data analytics pipelines

2.2: Creation and capture

Data assurance considerations
Data gathering methods

2.3: Storage

Data storage considerations

2.4: Data transformation

Data wrangling and maintenance

2.5: Usage and analytics

Data usage and analytics

2.6: Usage and visualisation

Presenting and visualising data

2.7: Archival

Data archiving methods

2.8: Destruction

Data destruction methods

3.1: Application Programming Interfaces (API)

Application Programming Interfaces (APIs)

3.2: User access controls

Types of user access control

3.3: Permissions

User and administrator rights

4.1: Legislation and the role of the ICO when using data

Computer Misuse Act (CMA)
Data Protection Act (DPA)
Freedom of Information Act (FOIA)
UK General Data Protection Legislation (UK GDPR)
Privacy and Electronic Communications Regulations (PECR)
Information Commissioner's Office (ICO)

5.1: Job roles related to data analytics

5.2: Personal attributes

Personal attributes

5.3: Communication skills

Communication skills