Expertise
Understand
the question
01
What question needs to be answered, what data is available, and what benefit should the solution provide?
Develop a solution
03
The appropriate data solution is implemented technically, for example as analysis, dashboard, data model, automation or tool.
Define the project goal
02
The objective, scope, data sources, and deliverable format are clearly defined. Depending on the scope, the implementation is divided into one or more work packages so that each deliverable can be specifically planned and implemented.
Provide the result
04
The solution is documented in a comprehensible manner and made available in such a way that it can be used in everyday work.
Data solutions. Clearly scoped.
Fixed price.
Good data solutions arise from clear questions. First, it is determined which question needs to be answered, which data is relevant, and what goal should be achieved.
This results in a structured solution that is implemented in a comprehensible manner and geared towards later use in the company.
The end result is a documented outcome that can be used in everyday work.
Work packages instead of large data projects
Many data projects lose momentum early on because coordination, project structures and effort become greater than the actual question being addressed.
Heisel Analytics' approach is deliberately lean: specific questions are translated into clearly defined work packages that end with a usable result.
Direct collaboration, short decision-making processes, and focused implementation ensure that efforts remain where they generate the greatest benefit: in the expert analysis, the technical implementation, and the delivery of a solution that can be used within the company. The strength lies in quickly familiarizing oneself with new issues, understanding the interrelationships, and developing pragmatic data solutions.
Workflow
Recent projects
About me
I am Oliver Heisel , founder of Heisel Analytics . My professional background combines business administration expertise with data science, data engineering, and the development of practical data solutions.
I have been working with data since 2019. My journey began with classic analyses, Excel models, and business-related questions. Over time, this has evolved into projects involving Python, SQL, data preparation, and data pipelines, culminating in sophisticated dashboards and key performance indicator (KPI) systems in the operational airline environment.
What particularly interests me about data projects is the combination of subject-matter expertise, analytical thinking, and technical development. I quickly familiarize myself with new topics, structure complex data sets, and develop solutions that not only work technically but can also be used practically within the company.
With Heisel Analytics, I pursue a deliberately focused approach. Many companies don't immediately need large data programs, but rather fast, clearly defined solutions for specific questions. This is precisely where I come in: with direct collaboration, clearly defined work packages, and transparently documented results.
Outside of traditional data projects, I am also deeply involved in technical topics, especially 3D printing, electronics, and open-source applications. As a regatta sailor and youth coach, it is also important to me to explain complex concepts clearly and make solutions practically applicable.
Oliver Heisel
MSc Data Science
BA Business Administration
Performance coach sailing
German (native speaker)
English C1 level, fluent in negotiations
