Using SQL for accessing and working with large administrative data in TREs

ObjectivesThe objective of this presentation is two-fold. First, it will explain why SQL is needed for large admin data provision and how this is operationalised in practice in TREs. Second, it will provide researchers with guidance and instructions for manipulating, cleaning and analysing data in SQL. MethodAdministrative datasets such as the invaluable Longitudinal Education Outcomes (LEO) are characterized by very large size and number of variables, as well as deep row counts. This entails it is not suitable to be provisioned via means such as flat files and software more familiar to researchers, such as STATA, SPSS or R. SQL is a valuable and sometimes indispensable tool for the provision of such data, as it can provide adequate storage, selective access to prevent disclosure risk and tools for data manipulation. The presentation will also cover weaknesses of SQL and when other software is more appropriate to use. ResultsThrough this presentation, we hope to ensure researchers will have a much better understanding of how and why data is provisioned through SQL, especially large administrative datasets. They will also learn techniques and principles of SQL usage, alongside useful pieces of code and syntax. In addition, the presentation will highlight when SQL should be used and when it is time to employ a different software, as it has its distinct strengths and weaknesses. ConclusionThrough understanding the use of SQL to access, manipulate and analyse large administrative datasets in TREs, researchers will be able to maximise the potential of their research and have a better experience overall.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3188
Primary Topic
Distributed and Parallel Computing Systems
Type
article
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article

Using SQL for accessing and working with large administrative data in TREs

Tudor Vilcan
International Journal for Population Data Science
Distributed and Parallel Computing Systems
article

Using SQL for accessing and working with large administrative data in TREs

Tudor Vilcan
article en

Abstract

ObjectivesThe objective of this presentation is two-fold. First, it will explain why SQL is needed for large admin data provision and how this is operationalised in practice in TREs. Second, it will provide researchers with guidance and instructions for manipulating, cleaning and analysing data in SQL. MethodAdministrative datasets such as the invaluable Longitudinal Education Outcomes (LEO) are characterized by very large size and number of variables, as well as deep row counts. This entails it is not suitable to be provisioned via means such as flat files and software more familiar to researchers, such as STATA, SPSS or R. SQL is a valuable and sometimes indispensable tool for the provision of such data, as it can provide adequate storage, selective access to prevent disclosure risk and tools for data manipulation. The presentation will also cover weaknesses of SQL and when other software is more appropriate to use. ResultsThrough this presentation, we hope to ensure researchers will have a much better understanding of how and why data is provisioned through SQL, especially large administrative datasets. They will also learn techniques and principles of SQL usage, alongside useful pieces of code and syntax. In addition, the presentation will highlight when SQL should be used and when it is time to employ a different software, as it has its distinct strengths and weaknesses. ConclusionThrough understanding the use of SQL to access, manipulate and analyse large administrative datasets in TREs, researchers will be able to maximise the potential of their research and have a better experience overall.

International Journal for Population Data ScienceVol. 10(4)
Office for National Statistics (GB)
Openalex Percentile: Top 75%
Distributed and Parallel Computing Systems
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Using SQL for accessing and working with large administrative data in TREs — Tudor Vilcan · International Journal for Population Data Science (2025) | TGRS Research Map | TGRS