## **Learning Outcomes**

After reading this article, you will be able to distinguish data, information, and knowledge in a business context. You will understand the stages of the data lifecycle, the attributes of good quality information, and practical data governance principles including laws, controls, and responsibilities. By the end, you should be able to explain how organisations ensure reliable, secure, and ethical handling of data throughout its lifecycle, and apply key concepts in ACCA exam situations.

## **ACCA Business and Technology (BT) Syllabus**

For ACCA Business and Technology (BT), you are required to understand how organisations collect, process, secure, and use data, and how they ensure quality and legal compliance through data governance. This article covers:

- The differences and relationship between data, information, and knowledge
- The stages of the data lifecycle: collection, processing, storage, use, sharing, and disposal
- Attributes of good information (ACCURATE)
- Data governance frameworks and responsibilities
- Laws and ethical principles relating to data protection and security
- Data quality control and risk management in business

## **Test Your Knowledge**

_Attempt these questions before reading this article. If you find some difficult or cannot remember the answers, remember to look more closely at that area during your revision._

1. Define the terms data, information, and knowledge. Give an example of each in a business scenario.
2. List the main stages of the data lifecycle and state a key risk or control required at two of these stages.
3. Which of the following is NOT a characteristic of good information as required by business users?  
   A) Accuracy  
   B) Timeliness  
   C) Excess detail  
   D) Relevance
4. State one legal obligation an organisation has under typical data protection laws at the data storage stage.
5. What is data governance and why is it important for organisations?

## **Introduction**

Information supports almost every decision and process in an organisation. However, the quality and security of this information depends on how data is collected, processed, and governed throughout its life. Understanding the distinctions between raw data, processed information, and organisational knowledge is fundamental for ACCA students. This article defines these concepts, explains the complete data lifecycle, and outlines the core principles of good data governance—combining practical business requirements with legal and ethical obligations.

> **Key Term: Data**  
> Raw, unprocessed facts, figures, or symbols—such as numbers, dates, or codes—recorded but not yet interpreted or put in context.
>
> **Key Term: Information**  
> Data that has been processed, organised, or structured so that it has meaning for the recipient and can support decision-making.
>
> **Key Term: Knowledge**  
> The application, analysis, or evaluation of information, typically including experience, context, and perception, to inform decisions or actions.

## **The Relationship Between Data, Information, and Knowledge**

Organisations transform data into useful information and ultimately knowledge, which supports better performance and decision-making.

- **Data:** "326," "2024/05/15," "Approved"—on their own, these values lack meaning.
- **Information:** When processed, the system generates a report stating, "326 units approved for dispatch on 2024/05/15."
- **Knowledge:** An experienced manager recognises that sales consistently increase in May, so recommends adjusting future production schedules accordingly.

A clear understanding of these distinctions is essential for ensuring that business systems produce outputs that are relevant, actionable, and secure.

### **Worked Example 1.1**

**Scenario:** A retailer collects daily sales figures (data). The finance team reviews a summary of daily sales by product line (information). The sales manager uses these summaries to decide which product lines to highlight next month (knowledge).

> **Answer:** The daily sales entries are data; the daily summaries are information; the decision to highlight is an application of knowledge.

## **The Data Lifecycle**

The data lifecycle describes the journey of data from its initial creation or receipt through to its ultimate disposal or secure destruction.

**Key stages:**

1. **Data Creation/Collection:** Data is generated or collected from internal or external sources (e.g., customer forms, transaction logs, external suppliers).
2. **Data Processing:** Data is validated, classified, and converted into meaningful information through calculations, grouping, and analysis.
3. **Data Storage:** Processed data and information are kept in databases, files, or cloud systems. Security and accessibility are key controls here.
4. **Data Use/Sharing:** Information is accessed, analysed, or distributed within or outside the organisation (e.g., reporting, meetings, regulatory submissions).
5. **Data Retention:** Organisations keep data for defined periods under legal, operational, or business policy requirements.
6. **Data Disposal/Destruction:** When no longer needed or legally required, data is deleted or destroyed using secure procedures to prevent unauthorised recovery.

> **Key Term: Data Lifecycle**  
> The sequence of stages through which data passes, from creation and initial storage to eventual disposal or permanent archive.

### **Worked Example 1.2**

**Question:** Identify controls a business should use when sharing sensitive payroll data with an external payroll service.

> **Answer:** Encrypt files during transfer, restrict access to authorised personnel, formalise a data processing agreement, and confirm secure deletion after use.

## **Attributes of Good Information**

Organisations rely on information that is both useful and trustworthy. Good information for decision-making should meet the ACCURATE criteria:

- **Accurate:** Free from significant errors or omissions.
- **Complete:** Contains all necessary details.
- **Cost-effective:** The cost of producing the information does not outweigh its value.
- **Understandable:** Presented clearly and suited to the user's needs.
- **Relevant:** Focused only on what is required.
- **Adaptable:** Can be updated or customised if business needs change.
- **Timely:** Provided in time to support decisions.
- **Easy to use:** Simple to access and interpret.

## **Data Governance**

Data governance brings together the people, processes, and technologies that ensure the quality, security, and legal compliance of organisational data throughout its lifecycle.

> **Key Term: Data Governance**  
> The system of rules, roles, and procedures that control how data is managed, protected, and used within an organisation to meet business, regulatory, and ethical requirements.

Well-designed data governance frameworks address:

- **Ownership and Accountability:** Assigning responsibility for data quality and security to individuals such as data owners or data stewards.
- **Policies and Procedures:** Establishing rules on data access, handling, consent, and disposal.
- **Risk Management:** Identifying and managing risks of loss, misuse, or unauthorised access.
- **Enforcement:** Monitoring and auditing compliance with policies and relevant legislation.

### **Worked Example 1.3**

**Question:** What is the impact of not having clear data governance on a firm handling personal customer data?

> **Answer:** Increased risk of data breaches, regulatory fines for non-compliance, reduced trust from customers and partners, and potential financial/legal liabilities.

## **Legal and Ethical Obligations in Data Governance**

All organisations must follow data protection legislation and security standards to safeguard personal and sensitive data at every data lifecycle stage.

Typical legal requirements include:

- Collecting data for specific, legitimate purposes with the subject’s consent.
- Keeping data accurate and up to date.
- Restricting data retention to the minimum time necessary.
- Implementing robust security controls (e.g., encryption, access control, secure disposal).
- Reporting breaches to authorities and affected parties as required by law.

Personal data must only be processed according to the rights of individuals, including the right to access, correct, or erase data, and the right to know how their data is used.

> **Key Term: Data Protection**  
> The act of securing personal data against misuse, loss, or unauthorised access, guided by laws and regulations.
>
> **Key Term: Data Security**  
> The set of technologies, processes, and policies that protect data from unauthorised access, theft, alteration, or destruction.

### **Exam Warning**

> Failure to apply proper data governance, even by accident, can lead to significant legal penalties for both organisations and individual managers. For ACCA exams, always consider legal, ethical, and internal policy dimensions—not just technical steps.

## **Data Quality and Controls**

Data quality management is essential for reliable information production. Organisations use various controls at each stage:

- **Validation Controls:** Automated checks on format, range, and completeness during data entry.
- **Access Controls:** Restricting who is authorised to view or modify particular data.
- **Audit Trails:** Recording changes, access, and transfers to detect errors or fraud.
- **Regular Reviews:** Periodically checking stored data for accuracy, duplication, or obsolete content.

Poor data quality can cause wrong business decisions, non-compliance, and reputational damage.

### **Revision Tip**

> When revising data lifecycle questions, memorise the stages and at least one key control or risk for each. Relate controls to ACCURATE attributes.

## **Summary**

Data, information, and knowledge are different but connected concepts that drive decisions in business. Data passes through a lifecycle—from collection to secure disposal—requiring strong controls at every step to ensure accuracy, completeness, and security. Effective data governance assigns responsibility, maintains quality, assures legal compliance, and protects stakeholder interests. Understanding these principles is essential for the ACCA exam and real-world practice.

## **Key Point Checklist**

_This article has covered the following key knowledge points:_

- Distinguish between data, information, and knowledge in business settings
- Describe the full data lifecycle and key controls at each stage
- List and explain the ACCURATE attributes of good information
- Define data governance and its practical importance for quality and compliance
- Summarise key legal and ethical requirements for data protection and security
- Identify measures to maintain high data quality and information reliability

## **Key Terms and Concepts**

- Data
- Information
- Knowledge
- Data Lifecycle
- Data Governance
- Data Protection
- Data Security

Data information and knowledge - Data lifecycle and governance