About

About Our Business

For several years now, operating on the IT market in Poland and beyond, we have observed that many data-related companies either merely hire IT specialists without actually taking any responsibility for the outcome of their work, or focus on the implementation of ‘Proof of concept’ class projects, which in reality turn out to be useless in business environment.

Finding a reliable and experienced partner who can provide support with expertise or even guide through the meanderings of data-driven projects is difficult. Therefore, many organisations are trying to implement such projects on their own. The results of such an approach are often unsatisfactory, as building even a small data warehouse to be business-functional requires a right dose of experience and standardisation.

In response to these observations and challenges, we established Data by Example – a company created by professionals with many years of experience in complex data processing projects. We want to support our Clients in building a competitive advantage based on their data in a comprehensive and high-quality manner.

Our values

Listening Partnership

At Data by Example, we have remembered from the very beginning that IT is a service supporting business growth. The aim of IT projects is to achieve a tangible return on investment, and the technology and implementation themselves must always be the best possible way to achieve a business outcome. Understanding the Client’s needs, developing concepts and putting ideas into practice to deliver the final expected value requires a partnership and an open approach, and these are underpinned by the ability not only to ask the right questions, but above all to listen.

Advice Trust

At Data by Example, we believe that experience is the key to solving business problems and delivering value. It is on this that trust is based. That is why we share with our Clients the standards and good practices we have developed over the years. We support projects with our technological and domain knowledge, proactive ideas and recommendations, resulting from our data expertise. We know that trust is born over time, both with successes achieved together and difficulties overcome. That is why, at Data by Example, we focus on long-term cooperation, where Clients can count on our professional advice. This is a particularly important aspect in the context of data, not only because the time it takes to introduce a specialist in this area is longer than in other IT specialisations, but above all because without trust, data activities simply have no chance of success.

Delivery Quality

In an age of focus on outsourcing programmers, at Data by Example we want more. We take responsibility not only for the attitude and skills of the delivered specialists, but above all for the final result of the project and its business value. Compromising at the expense of quality in IT projects is, according to our philosophy, a very short-term strategy that we are strongly wary of. We believe that our Clients deserve more and therefore we expect and demand more from ourselves. Improving ourselves, keeping abreast of technology, looking ahead with concepts and improvements, dynamism and flexibility are just some of our principles. We change the world by starting with ourselves, and acting ‘by example’ is part of our journey to co-create the vastness of opportunities for turning data into information.

How We Work

Project Management

Years of experience in IT projects have led us to develop a way of managing projects that combines the best practices of agile management with a classical approach.

Our teams use daily meetings with the project manager and product owner, planning the work in sprints using agile tools and, if needed, meetings to assess the progress of the work and discuss any problems within the team.

On the other hand, we know that IT projects are not lonely islands and that decision-makers in organisations need precise information about the schedule, budget and scope of the project. We therefore overlay a layer of classic project management with multi-level communication and regular steering committee meetings on top of the day-to-day agile operations of the teams.

Our experience confirms that such a combination of agile and classic methods is the most effective way to implement projects in the data area.

Teams

We follow two basic principles when managing teams delivering projects in the data area.

Firstly, the team must be selected in terms of skills and experience appropriate to the value to be delivered by the project. At the project planning stage, we determine whether we will be building new environments and thus the involvement of a devops specialist is necessary, whether the data models will be for analytical use or just for data security, which in turn influences the decision to involve a data analyst in the project. A properly composed team is a guarantee that the work will run smoothly and be carried out at the right level.

On the other hand, our experience has taught us that IT projects cannot be implemented without the involvement of four key roles:

Product Owner who understands the solution being built and its business relevance
Project Manager responsible for project scope, schedule and budget
Architect responsible for the scalability and security of the system and the selection of appropriate technologies for its implementation
Lead Developer to control the quality of the solution and implement the project to the best standards

These roles do not need to be involved in the project full time, but their absence significantly compromises the final outcome of the project.

Standards

Hundreds of completed projects in the data area have allowed us to develop numerous standards of work in the areas of data analysis and modelling, system architecture design, constructing environments and ensuring their security, creating and testing data transformation code, data quality control and assurance, creating visually appealing yet useful reports, building applications and user interfaces based on big data, and creating, running and maintaining artificial intelligence models.

Thanks to the existence of this standardisation of work, it is possible to implement projects, not only within the planned schedules and budgets, but above all at the right quality. This quality, in turn, ensures that the completed project delivers the expected return on investment and contributes to a data-driven competitive advantage.