Navigating the World of Secondary Data: Hands-on Experience
Global Research & Training
New Delhi
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Navigating the World of Secondary Data: Hands-on Experience
Introduction to Data
- Generally, data refers to facts, figures, and statistics collected for reference or analysis.
- But in research, data is much more than numbers. it’s evidence. It’s the raw material that we process to extract meaningful insights.
- It tells about Who We Are? And How Much We Are? In terms of gender, region, religion, and its quantity.
- Secondary data refers to information that was collected by someone else for a different purpose but now it will be use by another researcher.
- In other words, Researcher do not collect it directly, but he or she use it for their research purpose.
Examples:
Data collected from government reports, surveys, or census data.
Published articles, academic journals, books, and reports from organizations.
Ø Pre-existing datasets available on data-sharing platforms or government websites.
- The United Nations defines data as “characteristics or information, usually numerical, that are collected through observation.”
- Burns and Bush (2010): Secondary data is data that were originally collected for a different research question or objective but can be used for new analysis.
- Babbie (2013): Secondary data are "Data collected by someone other than the user.“
- Creswell (2014): Secondary data are data that were collected previously by other researchers or organizations for different research objectives.
- Indian Government Database
- International Database
- Private Database
- Literature Database
Based on Collection Method
When we talk about data collection, there are two broad categories: Primary Data and Secondary Data
Primary Data:
Collected directly by the researcher for a
specific purpose.
Examples: Surveys you design yourself,
interviews you conduct, field observations.
Pros: Tailored to your needs; you control
the quality.
Cons: Time-consuming, costly, and
resource-intensive.
Secondary Data
Collected by someone else for a different
purpose, but available for your use.
Examples: Census of India, World Bank
Indicators, NSSO surveys, WHO health statistics.
Pros: Saves time and cost; often covers
large populations over many years.
Cons: May not match your exact needs; limited control over how it was collected.
Examples:Data collected from government reports, surveys, or census data.
Published articles, academic journals, books, and reports from organizations.
Pre-existing datasets available on data-sharing platforms or government websites.
Types of data collection:
Census Data
Data collected from every unit in a population (e.g., all households in a country).
Sample Data
Data collected from a sample of the population, often with specialized focus (e.g., health surveys, labor force surveys).
Administrative Data
Information gathered through government records and databases (e.g., tax records, school enrollments).
Unit-Level Data vs. Aggregate Data
Unit-Level data:
Contains detailed, disaggregated
information at the establishment or unit level.
Data at the firm or household level, e.g., fixed capital, working capital, output, employment …etc. at a factory level.
Aggregate data:
Summarized data across establishments,
e.g., total employment in a region or sector.
For example, aggregate data might show the total number of workers in the manufacturing sector in a given region, without showing data for individual factories.
Quantitative Data
◦
Numerical in nature; can be measured and
analyzed statistically.
◦
Examples: GDP growth rate, literacy rate,
rainfall in mm.
Qualitative Data
◦
Descriptive, categorical, or non-numerical
information.
◦
Examples: Gender, occupation type, political
affiliation.
◦
Often coded into numbers for analysis.
Types of Secondary Data
1.
Time-Series
Data:
Data
collected and recorded over a specific period at regular intervals (e.g.,
annually, quarterly, monthly), Decade.
Examples include: Annual GDP data for a country over several years, Population census over decades
2.
Cross-sectional Data:
Data
collected at a single point in time across multiple entities (population,
literacy rate, unemployment rate, etc.).
Examples include: Education levels across different regions in 2024, HDI value across Asian counties in 2024.
3.
Panel Data (Longitudinal Data)
A
combination of time series and cross-sectional data, where data is collected
for the same entities (individuals, regions, countries, etc.) over multiple
time periods.
Example include: HDI values for India, Pakistan, Bangladesh, Nepal, and Sri Lanka from 2007–2022.
Comparison of Types | |||
Feature | Time Series | Cross-Sectional | Panel Data |
Dimension | Single entity, multiple times | Multiple entities, single time | Multiple entities, multiple times |
Importance of Secondary Data
1.
Cost-Effective:
Secondary data is cost-saving and often freely available or comes at a low cost. It is more affordable option, especially for researchers working with limited budgets.
2.
Time-Saving:
Secondary data is already available and can be used immediately which can save substantial time.
3.
Large Scale and Comprehensive:
Secondary data often provides access to
large datasets, offering broad coverage across multiple regions, time periods,
or demographic groups.
4.
Cross-Disciplinary
Research:
Secondary data can be used across different research disciplines.
Advantages and Limitations of Secondary Data
Advantages
Saves time and cost.
Often collected by reputable agencies with large
resources.
Enables long-term trend analysis.
Offers large sample sizes and broad coverage.
Limitations
May not exactly match your research question.
Possible issues with outdated data.
Quality depends on original collection methods.
Sometimes incomplete or missing variables you
need.
How to Choose the Right Dataset
When selecting a dataset:
Relevance: Does it match your topic,
geography, and time period?
Coverage: Is the population/sample
adequate for your analysis?
Accuracy & Credibility: Was it
collected by a trusted source?
Level of detail: Unit-level vs aggregated
— which do you need?
Format & Accessibility: Can you
easily open and process it?
Licensing: Are there usage restrictions?
Ethical Considerations:
1.
Data Privacy and Confidentiality:
Researchers must ensure that privacy and confidentiality are maintained. The use of such data should comply with ethical standards and data protection regulations (e.g., PDPA (Personal Data Protection Act) and General Data Protection Regulation (GDPR) etc.
2.
Acknowledging Sources and Copyright:
Using
secondary data ethically means giving proper credit to the original creators or
collectors of the data. This shows respect for their work and helps avoid
plagiarism.
Secondary Data in India: Key Sources
India offers several open data platforms
through its government websites. Thes data span multiple sectors,
including demographics, economics, health, education, and more. Key
sources include the Census of India, MoSPI (ASI, PLFS, NSS, IIP,
Economic Census…etc.), NFHS, RBI, AISHE, USISE+, NDAP
(NITI Aayog’s database), Data.Gov etc.
International
Secondary Data: Key Sources
Several international organizations and universities offer
open data platforms through its databases or portal. Thes data
span multiple sectors, including demographics, economics, social, health,
education, and more. Key sources for
international secondary data include the United Nations database, World Bank
database, International Labour Organization database, World Health Organization
database International Monetary Fund database and FAOStat databse ...etc.
Key Private Data Sources:
1. EPWRF:
2. Centre
for Monitoring Indian Economy (CMIE):
Economic Outlook (CMIE):
CPDx– Consumer Pyramids Dx (CMIE)
ProwessIQ (CMIE
3. Indiastat database
Indiastat Districts database:
Indiastat elections:
4. Indian Marketing Intelligence (MICA)
database:
Literature
Database: Key Sources
Key
literature data sources include peer-reviewed journals, books, and conference
proceedings, as well as online databases that provide comprehensive access to
scholarly material. Notable databases include Sodh Ganga (a reservoir of
theses), Sodh Gangotri (a repository of synopses), Google Scholar,
JSTOR, Science Direct, ResearchGate, and Academia.edu
etc., all of which serve as rich repositories for academic literature
across disciplines. These platforms offer diverse, reliable materials essential
for robust research.
For more details on the data sources and its links, please visit
this article.
https://grtedu.blogspot.com/2025/01/name-of-secondary-data-sources-and-its.html
Thank
You and Best Wishes
Raghavendra Yadav
Global
Research & Training, New Delhi
Email: info@grtedu.com | Web: www.grtedu.com
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