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Reykholt Data was founded out of a passion for Python programming and a belief that even the smallest businesses deserve access to the same data tools as larger organisations. At the moment, Reykholt Data is run by a single independent freelancer - but the vision is to grow into a small, agile consultancy that helps businesses of all sizes make better use of their data.
I specialise in creating low-cost, automated Python solutions that save you time and reduce manual effort, whether that’s transforming spreadsheets, streamlining database processes, or building custom ETL (Extract, Transform, Load) workflows. The goal is simple: reduce repetitive tasks so you can focus on growing your business.
Projects can be as small as a single automated script - for example, cleaning up and joining Excel files in seconds rather than hours - or more complex solutions that integrate with your existing databases and reporting tools. Once built, these automations can be reused as often as you like, with no extra cost.
For data visualisation, I can also help build insightful dashboards in Power BI (see licencing details here) or use Python’s own powerful (and free) visualisation libraries.
Why Python?
Python has become the industry standard for solving data problems - from simple but essential tasks like cleaning Excel files and merging datasets, to building complete ETL pipelines that move data between databases and systems. By using Python’s free, open-source tools, I can deliver solutions that are flexible, cost-effective and easy to scale as your needs grow.
There’s very little that Python can’t do. In fact, I created this website using Python + Flask (another opportunity to learn a new skill). If you’re new to Python, the resources below will give you a sense of how it can help streamline your business processes.
Extracting data
Before data can be transformed, it first needs to be reliably extracted from its source. Python offers a wide range of tools for this step - from reading CSV and Excel files with Pandas, to connecting directly to databases using libraries such as SQLAlchemy or psycopg2. It can also handle data from APIs and even scrape structured content from the web when needed. This flexibility ensures that no matter where your data lives, it can be programmatically retrieved and prepared for the next stage of analysis.
How I can help: I develop custom Python scripts that securely and efficiently extract data from the sources you rely on most. Whether your information is spread across Excel spreadsheets, relational databases, or online APIs, I’ll build extraction pipelines that are robust, repeatable and tailored to your business. This saves you time compared to manual exports and ensures you always have up-to-date, accurate datasets ready for transformation and reporting.
Transforming data
Once data is extracted, transforming it into a usable format is crucial. Python's Pandas library is the industry standard for this step, offering a highly efficient and intuitive way to clean, reshape and aggregate data. You can handle missing values, filter data, merge multiple datasets and perform complex calculations with ease using its powerful DataFrame object.
How I can help: I develop Python transformation scripts that clean, enrich and standardise your data. I’ll work with you to define the business rules and logic needed to prepare your data, making sure it’s accurate, consistent and ready for reporting or business intelligence tools. These scripts can handle multiple files at once, saving valuable hours and reducing the risk of human error.
Loading data
The final step is loading the transformed data into a target destination. Python provides flexible options for this process. Psycopg2 and SQLAlchemy are popular choices for loading data into SQL databases. Similarly, libraries like boto3 are used for cloud storage services like Amazon S3 and pyodbc can connect to a wide range of databases. This versatility allows you to load data into a data warehouse, a data lake, or another application, ensuring the data is ready for analysis and reporting.
How I can help: I can design and write Python scripts that seamlessly load your processed data into your desired destination.
Open-source and cost-effective
One of Python's most significant advantages is that it is a free and open-source programming language. The core language and its vast ecosystem of libraries—including essential tools for ETL like Pandas and NumPy are available at no cost. This eliminates expensive licensing fees and proprietary vendor lock-in that are often associated with commercial ETL platforms. The Python Software Foundation (PSF) oversees its development under a permissive license, which means you can use it for any purpose, including commercial applications, without paying anything. This makes Python an incredibly cost-effective solution for businesses of all sizes.
How I can help: By leveraging Python’s open-source ecosystem, I build powerful and affordable solutions for your business. Instead of relying on costly proprietary software, I develop custom scripts using free, community-supported libraries. This keeps your costs low while giving you a flexible, transparent and highly adaptable setup that can grow with your needs.
Data analysis
Beyond data transformation, I help businesses unlock the full potential of their information through advanced data analysis and reporting. Using tools like Power BI, I design interactive dashboards and visualisations that turn raw datasets into clear, actionable insights. I also work with data schemas to structure and relate information effectively, ensuring reports are accurate, consistent and scalable. Whether it’s building KPIs, trend analyses, or complex drill-down views, my approach combines strong Python-based data preparation with intuitive, visually engaging reports. This gives decision-makers the ability to explore their data in real time, identify opportunities and track performance with confidence.