Unit 3: Data and Knowledge Management
In the information economy, data is one of an organization’s most valuable assets. However, raw data by itself is not useful. It must be effectively managed, processed, and transformed into knowledge to support business operations and strategic decision-making.
Figure 1: Data and Knowledge Management Overview
flowchart LR
subgraph JOURNEY["Data to Knowledge Journey"]
DATA["📝 Raw Data\nFacts & Figures"]
DB["🗃️ Database\nOrganized Storage"]
DW["🏭 Data Warehouse\nIntegrated Analysis"]
BI["📊 Business Intelligence\nInsights & Reports"]
KM["🧠 Knowledge\nActionable Expertise"]
end
DATA --> DB --> DW --> BI --> KM
style KM fill:#2d5016,color:#fff
Figure 2: The Data to Knowledge Pipeline
This unit covers the fundamentals of data and knowledge management. We will explore the challenges of managing data, the advantages of a structured database approach, and the rise of Big Data. We will also examine the concepts of data warehouses and data marts for analysis, and conclude with knowledge management—the process through which organizations capture, share, and leverage the collective expertise of their employees.
What This Unit Covers
| Chapter | Topic | Key question |
|---|---|---|
| 3.2 | Managing data | Why is managing data difficult, and what is data governance? |
| 3.3 | The database approach | How do databases and the relational model solve file-based problems? |
| 3.4 | Big Data | What makes data “big”, and how do firms use it? |
| 3.5 | Data warehouses and data marts | How is data prepared and stored for analysis? |
| 3.6 | Knowledge management | How do organizations capture and share what their people know? |
Why This Unit Matters
- Decisions are only as good as the data behind them. Duplicate, outdated, or inconsistent records lead to wrong decisions and unhappy customers.
- Almost every business application, from a shop’s billing software to a bank’s core system, stores its data in a database.
- Knowledge walks out of the door when experienced staff leave unless the firm deliberately captures and shares it.
Key Terms
| Term | Meaning |
|---|---|
| Data | Raw facts, such as a sale amount or a date |
| Information | Data organised so that it has meaning, such as monthly sales by branch |
| Knowledge | Information applied with experience to solve problems or make decisions |
| Database | An organised collection of related data managed by a DBMS |
| Data warehouse | A central store of cleaned, historical data from many sources, built for analysis |
| Big Data | Data too large, fast, or varied for traditional tools (the Vs: volume, velocity, variety, veracity, value) |
The Nepal Context
Nepali organisations generate large amounts of data: banks and wallets record millions of transactions, telecom operators record calls and data use, and hospitals and schools keep growing records. Yet many small firms still keep customer and stock records in notebooks and separate spreadsheets, which leads to duplicate and inconsistent data. The Privacy Act, 2075 (2018) adds a legal duty to protect personal data.
Key Takeaways
- Data is hard to manage because it grows quickly, is scattered across systems, and decays over time; data governance sets the policies that keep it accurate and secure.
- The database approach stores data once in shared, related tables, reducing the redundancy, inconsistency, and isolation of file-based systems.
- Big Data is defined by its volume, velocity, and variety (often extended with veracity and value) and needs new tools to store and analyse.
- Data warehouses and data marts hold cleaned, integrated, historical data prepared through ETL specifically for analysis rather than daily transactions.
- Knowledge management captures explicit and tacit knowledge so that expertise stays in the organization when people leave.
Unit Review Questions
Short answer
- Distinguish between data, information, and knowledge with examples.
- What is a data warehouse?
- List the Vs of Big Data.
Long answer
- Explain the difficulties of managing data and how the database approach addresses them.
- What is knowledge management? Explain the difference between explicit and tacit knowledge and how organizations can manage each.
