# Survey pipeline and qualitative analysis

> Transformation of survey exports into reviewable analytical outputs with Python, pandas, Excel and human judgement.

- URL: https://www.enter20.com/en/work/survey-qualitative-analysis/
- Español: https://www.enter20.com/trabajos/encuestas-analisis-cualitativo/
- enter 2.0 — Practical AI, governed data, dashboards, automation and information systems for organisations that need to make better decisions.

- Client type: Evaluation and social analysis project
- Technologies: Python, pandas, Parquet, Excel, CSV, pytest, R

## Problem

Open-ended responses and survey data needed coding, cleaning, traceability and understandable deliverables for later analysis.

## Constraints

- Open-ended responses with linguistic variation and interpretive judgement.
- Need to retain human review and not delegate conclusions to a black box.
- Deliverables in formats that non-technical users can handle.

## What was done

- Python scripts to import, clean, code and review data.
- Codebooks, review queues, audit of imputations and Excel outputs.
- Qualitative and quantitative synthesis with traceability of the process.
- Documentation so that the workflow can be repeated with new batches of data.

## Governance and security

- Human review at points of interpretive decision.
- Audit of imputations and exceptions.
- Separation of source data, processed data and deliverables.

## Result

The analysis moved from unwieldy exports to a reviewable, reusable base for conclusions, reports and improvements to the questionnaire.

## What it demonstrates

- Careful automation where context matters.
- Ability to combine qualitative and quantitative data.
- Delivery in formats that are useful to research or management teams.

## Connected areas

- [Data, indicators and dashboards](https://www.enter20.com/en/services/data-indicators-dashboards/)
- [Document and data automation](https://www.enter20.com/en/services/document-data-automation/)