All projects
D
Data / ETL

Data processing scripts and migration between databases

Clients needed to migrate data between incompatible systems, clean up polluted databases, or transform data formats. Automated tools replaced days of manual work with reliable processing that ran in a few minutes.

Data / ETL
2019-2020 Project duration
4 deliverables Features
3 outcomes Measured impact

The company had accumulated years of data in heterogeneous formats: MySQL databases, CSV files, XML exports, and semi-structured data from various systems. Migrating to a new infrastructure meant consolidating, cleaning and transforming this data without losing any of it.

The migration was carried out with an automated pipeline that extracts the source data, cleans it (duplicates, inconsistent formats, missing fields), transforms it to the target schema and loads it into the new PostgreSQL database. Integrity validation at each step ensures that no data is lost or corrupted.

What was delivered

Automated migrations between databases eliminated manual data-entry errors and guaranteed data integrity.

Automatic cleaning and validation detected and corrected inconsistencies that manual processing would have let through.

Reproducible, scheduled processing makes it possible to re-run operations at any time with the same reliable results.

Quality reports produce a complete summary for each run, giving confidence in the results.

Key results

Migration

Automated transfer

Cleaning

Clean data

Validation

Quality control

Technologies used

Python
Perl
Bash
MySQL
PostgreSQL
Role Backend Developer
Duration 2019-2020
Engagement Freelance contracts (Tier D)

A similar project?

Let's talk through what you need - no commitment.