3.8 Data Systems

3.8.1 Data wrangling

Definition and Purpose of Data Wrangling
Data wrangling is the process of transforming raw data into a usable and meaningful format. It is used before analysis to improve data quality and consistency.

3.8.2 Steps of data wrangling

Structure
Structuring data involves organising it into a consistent format such as tables, fields, or records.
Clean
Cleaning data removes errors, duplicates, and incomplete values to improve reliability.
Validate
Validation checks that data meets defined rules such as correct type and acceptable range.
Enrich
Enrichment adds additional data or context to improve usefulness and value.
Output
The output stage prepares the final data set for storage, analysis, or reporting.

3.8.3 Core functions of a data system

Data System Functions
Core functions of a data system include:
  • Input – capturing data
  • Search – finding data
  • Save – storing data
  • Integrate – combining data from multiple sources
  • Organise (index) – structuring data for access
  • Output – presenting data
  • Feedback loop – using outputs to improve future inputs

3.8.4 Types of data entry errors

Transcription Errors
Transcription errors occur when data is entered incorrectly, such as typing the wrong characters.
Transposition Errors
Transposition errors occur when digits or characters are entered in the wrong order.

3.8.5 Reducing data entry errors

Error Reduction Methods
Methods to reduce data entry errors include:
  • Validation of user input
  • Verification through double entry
  • Drop‑down menus
  • Pre‑filled data entry boxes

3.8.6 Factors impacting data entry implementation

Implementation Factors
Data entry implementation is affected by:
  • Time needed to design input screens
  • Expertise required to develop screens
  • Time required for data entry

3.8.7 Data entry factors and data quality

Data Quality and Error Reduction
Data quality is directly affected by how data is entered. Organisations must select suitable error‑reduction methods to balance accuracy, efficiency, and cost.

3.8.8 Suitability of data entry implementation

Making Judgements About Data Entry
When implementing data entry solutions, organisations must consider time, expertise, and impact on data quality to determine suitability within digital support and security environments.