Data Engineering

A clear vision in a complicated world

Data engineers are also called architects because they create an integral picture of how different data sources and applications can be joined together. How to transfer data from one system to another, merge different systems, model, organise, balance, automate, migrate and integrate data? Let us work it out for you.

Data engineering separates the wheat from the chaff

Data volumes double every two years. This makes it increasingly difficult to find the “right” data, and it is easy to get lost in the decision-making process because data are fractured and do not form an integral whole. Without a helicopter view and an overview of the actual situation, business problems are often solved manually and one by one.

The economic situation is in a constant change – especially these days. When you need to make quick decisions, does it take a lot of time to gather data and order reports, meaning the reliability of the end result is often questionable? Your credibility in the eyes of your clients and partners today and tomorrow depends greatly on the quality of your data and the way you use it.

How do we do it?

  • We don’t build solutions just for the sake of building. We build solutions to match your most primary and pressing needs, and we make the process as fast and robust as possible. 

  • We make sure you start using the data early on. If necessary, we adjust the direction as we go on, because we don’t necessarily have to build the different “tiers” of the solution in the right order – that’s the beauty of the gradual development process. 

  • The entire process is monitorable, transparent and easy to understand, because you’re involved in it. Eventually, it will be your data solution, not ours. 

Sound like rocket science?

Yes, we do use the newest approaches, technologies, processes and tools to solve data-technical challenges. 

However, the real aim is always to solve your business problem. 

Pipelines, orchestration, metadata, ETL/ELT (Extract, Transformation, Load) processes, analytical databases, etc. – these are the key components of data warehouse projects. A reverse process (reverse ETL) means that data are transferred from the data warehouse back to operational applications (sales, marketing, customer service). We could go on writing about this for a while, but perhaps it would be a better idea to meet up and talk about your needs.

Tiit Anmann

Sales and Business Development

Data engineering is a process that constantly seeks new opportunities to use data so that they create value for the company’s clients, as well as for different internal processes.

The process of our data project


Determining the business needs

What is it that your company needs? Getting the business problem defined also opens the way for a detailed action plan.



Understanding and preparing data

Which data are accessible? What is their quality? In what format do we need them?

How can we process them further? Merging. Conversions. Calculations.


Creating the solution

Based on the business goals, we design the fastest and most easily implemented initial solution.

We assess how it corresponds to the goals set. We amend, improve, test again.



How to deliver the maximum to different users? We install, configure, train, guide, listen, amend.

Get in touch!

How could we boost your organisation’s business?

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