Innovation Guide:
Transforming IT systems
into agile data hubs

Krzysztof Szromek CTO

The transformation of systems into data hubs is a development direction that should definitely be taken into account. The balance of potential gains and losses is clearly in favor of this solution, which can already be seen in the current trends, as well as the dynamic development of the cloud computing market in the field of data processing.

Learn how to bring more innovation into existing IT services – download the guide.

Table of Contents:

  1. Risks of siloed systems
  2. Documenting data life-cyclein agile IT services
  3. Easing out innovation costs with simple 3-steps methodology
  4. Data types & data extraction technologies/services
  5. Transparent and automated data flows
  6. Effective data distribution framework & possible uses
  7. Security, performance and maintenance challenges you may face (with solutions)

Strong awareness of the value of the raw material, i.e. data, and its usefulness in optimizing business processes, leads to the transformation of current systems into agile data hubs. Although this project is associated with a number of technical challenges (but not just that!), there is no doubt that in the long run – it simply pays off. The flexibility and scalability of such data hubs also facilitate future development and allows the company to focus on providing customers with high-quality solutions and services as a top priority. Creating an agile data hub eliminates all the problems concerning siloed systems.

About the author:

Krzysztof Szromek,  CTO at Exlabs Software Ltd

Technology leader focused on evaluating technology strategies and technical team management. Aims to leverage existing products and solutions to accelerate business
product delivery and seize new opportunities. For over 10 years delivering connected web platforms, managing engineering teams, and advising on software strategies for the SMB sector. Former programming expert with experience in working with a wide range of companies. Helps managers to navigate the modern market and manage technological strategies.

View Krzysztof’s profile on LinkedIn.

It is also worth knowing that there are plenty of solutions offered by tech giants today that greatly improve and facilitate such transformation of existing systems into data hubs. Cloud platforms and generally understood cloud computing already offers a whole range of tools that support data analysis, data processing, and automation of data flows between specific services. Companies no longer have to build expensive infrastructure from scratch. All you need is the right specialists for selected cloud platforms who will implement specific solutions, making the creation of data hubs faster, cheaper (and safer).

You will learn about:

  • Data Flows – easing out innovation costs by sharing data across services
  • Machine Learning – extracting data from media files
  • C4 Model – architecture described at four different levels of granularity
  • API – available technologies & how to design effective API architecture

More and more stringent legal regulations in the field of data collection and processing require companies to apply specific procedures and caution in this regard. Although limiting the possibility of collecting data for users is undoubtedly a beneficial phenomenon, it also creates new challenges for companies.