Sources of Data in Commerce: Types, Methods & Examples

Sources of data are fundamental in Commerce, Statistics, and Business Studies. They represent the origin points—physical or digital—where information is stored for research, analysis, and informed decision-making. Data is the backbone of planning, forecasting, and assessing trends. A reliable source of data enables organisations and students to interpret information accurately for business, economics, and project work.

Definition and Importance

A source of data refers to any medium—such as a database, report, or record—where information is stored or accessed. In Commerce, sources help in gathering facts for financial reports, economic analysis, and managerial decisions. They can be internal (within the organisation) or external (outside references or publications). Understanding these helps students and professionals choose the right methods for collecting meaningful statistics.

Types of Data Sources

Data sources can broadly be classified as primary or secondary:

• Primary Data: Information collected firsthand by the researcher for a specific objective. Methods include direct surveys, interviews, and experiments within the organisation.
  Examples:

  • Sales force reports
  • Accounting records
  • Internal expert analysis
• Secondary Data: Data originally collected by someone else, often for a different purpose, and used for analysis by new users.
  Examples:

  • Government reports
  • Industry publications
  • Census documents
  • Non-government research

How Data is Collected

The main approaches for collecting data relate to the nature of the source. Primary data is obtained by internal research, such as direct surveys, while secondary data is often gathered from books, published records, or external agencies.

Examples of Data Sources

Consider a business tracking its product sales. The internal sales database records each transaction (primary data). Conversely, a researcher examining industry-wide trends may consult published census data or industry journals (secondary data). For instance, an online retailer's inventory database lets its website show customers product availability—a typical example of a digital data source.

Types of Data Collected

Commerce subjects use both qualitative and quantitative data:

• Quantitative data: Numeric values (e.g., sales figures, market shares).
• Qualitative data: Descriptive attributes or opinions (e.g., customer preferences).

Both types can be gathered via surveys, questionnaires, or observational studies.

Approaches to Data Collection in Research and Business

When organisations or students collect data, the process usually involves:

1. Identifying the research objective or business problem.
2. Selecting the right source (internal vs external).
3. Choosing suitable methods (survey, experiment, record analysis).
4. Collecting, organising, and preparing data for analysis.
5. Interpreting results for decision-making or reporting.

For official or broad-scale analysis, methods like the census (studying the entire population) or statistical surveys (studying a sample) are widely used. Some sample survey methods include questionnaires and interviews.

Key Experimental Approaches in Data Collection

When conducting experiments to collect data, researchers may use:

• Completely Randomized Design (CRD): Experiments are assigned at random, useful for comparisons.
• Randomized Block Design (RBD): Experiments divided into blocks for analysing group differences, common in business and agriculture.
• Latin Square Design: Experimental units arranged in rows and columns to control variation—helps in complex testing environments.
• Factorial Design: Tests two or more factors together to observe combined effects, supporting deeper statistical analysis.

Step-by-Step Example: Business Data Source Selection

Suppose a business wants to understand customer satisfaction:

1. Define the goal (measure customer satisfaction).
2. Choose internal data (customer feedback via survey as primary data).
3. Consider supplementing with industry benchmarks (external, secondary data).
4. Analyse the data for actionable insights.

Key Definitions and Applications

• Internal Source: Data from within an organisation (accounts, reports).
• External Source: Data found outside (government, publications).
• Statistical Survey: Collects data from a sample using methods like questionnaires.
• Census: Collects data from an entire population for official analysis.

Next Steps for Commerce Learners

• Practice identifying primary vs. secondary sources in real case studies.
• Use data tables and internal company records for sample analysis in projects.
• Review more on data types and analysis in advanced Commerce lessons.

For more on related foundational topics, visit these Vedantu resources:
Source of Energy, Energy Conversion, Conservation of Energy.