Digital information systems
Digital information systems looks at how an organisation collects, stores, retrieves and uses data: the components involved, how the data is structured, how quality and security are protected, and the social and legal implications.
Core rules and concepts
- Components of a system include hardware, software, data, people, procedures and networks; each can be a point of failure or risk.
- Structure data in related tables: a primary key uniquely identifies a row, a foreign key links to another table, and normalising removes repeated data that causes update, insertion and deletion anomalies.
- Validation checks that input follows rules (presence, type, range, format). Verification checks accuracy after entry (double entry, proofreading, check digits). They are not the same thing.
- Security covers authentication, access permissions, encryption and backups; privacy covers what is collected and how it is used. New Zealand's Privacy Act 2020 sets out privacy principles, including storage, access, correction and mandatory breach notification.
Worked example
A booking table stores customer name, address, email, date and event on every row. Reasoning: if a customer moves, every booking must be updated or the data conflicts (update anomaly); a new customer cannot be added before booking (insertion anomaly); deleting their last booking destroys their details (deletion anomaly). Split it into Customers(customer_id primary key, name, address, email) and Bookings(booking_id primary key, customer_id foreign key, date, event), then join on customer_id. Note that deliberate duplication can be justified for reporting speed.
Traps that cost marks
- Claiming validated data is automatically accurate.
- Confusing encryption with backups, or security with privacy.
- Describing anomalies in general terms instead of showing them in the given context.