Secondary Data Analysis in Business Decisions

Secondary Data Sources

Use of Tables

Tables categorize information and can be single or double entry. Their static nature presents summarized information in an orderly manner, which can be helpful for extensive data. However, tables may oversimplify information. They should support the report's details, not replace them, and always include explanatory comments.

Use of Layouts

Layouts illustrate complex relational and transformational processes. They offer a synthetic view of dynamic changes and developments. However, layouts require detailed explanations, similar to other graphical representations. Appropriate use enhances report comprehension and provides a global perspective.

Secondary Data Sources

Modern companies rely on reports and statistical data for government and business decisions. Secondary sources encompass diverse materials, with a focus here on quantitative or statistical sources.

Secondary Analysis and Sources

A secondary data source is an organized set of data or information units initially created for a purpose different from the researcher's current objective. Precautions are necessary when using data produced for other reasons.

Following J. Ibanez, empirical research and data production practices highlight that data isn't readily available but results from intellectual, physical, and social processes. Empirical research produces data to generate truth and power.

The distinction between data production and analysis forms an initial typology of secondary data analysis. This criterion replaces the researcher's perspective, as they are a second-order observer analyzing results from other observers, producing new data.

Secondary researchers can analyze their own data from previous investigations, although this is uncommon. Research is a continuous process where researchers' positions evolve with new knowledge, often appearing as primary analysis.

Official statistical sources, published by public institutions, are secondary statistical sources with social reality certification. Using secondary sources is a potential concretion of secondary analysis.

Secondary analysis is categorized into two types: secondary analysis of secondary information (A), which involves aggregated data (group-level, not individual) without prior analysis. This is the information researchers encounter in official statistical institute publications. This secondary information is often raw data collected for other purposes, without analysis beyond data matrix establishment (quantitative) or speech transcriptions (qualitative). This is considered poorly prepared secondary data (A1), produced for other purposes and found by the researcher.