From concept to implementation

Designing and Shaping Your
Data Platform

Overcome data swamps and master your data with your fully customized platform. Let’s enpower your teams to develop data intensive solutions in a decentralized and structured manner.

Data Platform Design

Data Platform Development

Application Development

Streamlining IT Projects

My Toolstack

What kind of questions do you have?

I have over 6 years of experience in the big data area and the same questions and problems often arise – click the options to see the solutions:

Over time, companies accumulate a variety of data and data sources. A data platform that consolidates and processes this data offers significant advantages. It not only allows a comprehensive view of the data, such as a 360-degree view of customers, but also enables the central implementation of important processes for data processing. This includes the use of machine learning models, data analysis, data engineering, visualizations, data governance and data management.

The consolidation of data on a central platform not only leads to process optimization, but also generates value that would not be feasible in isolated data silos. A data platform supports and improves all data-driven areas of a company.

Linking existing source systems directly for data exchange is not advisable because it can lead to confusion and operational issues. When systems are directly connected, it becomes hard to track and understand what each system is doing. This complexity can make it difficult to identify and resolve problems.

Furthermore, direct linking isn’t scalable. As a company grows and its data needs become more complex, these connections can become a bottleneck.

A better solution is to use a central data platform. This platform serves as a hub where all data is gathered, processed as needed, and then sent out. This approach allows for easier control and scaling of data processing, which is key for efficient data management and utilization. A central platform simplifies data flows, making it easier to manage and understand, and allows individual systems to operate independently.

The first step is to consider what type of data platform you want to develop. There are various approaches, each tailored to different requirements. Many data warehouse approaches have been successfully implemented in recent years. However, these approaches are often no longer sufficient in the age of big data. Alternative approaches such as data lake architectures, lakehouse architectures and data mesh architectures offer advantages over conventional architectures. I can help you to choose the right one for you.

The options for building a data platform vary greatly depending on the specific needs of your company. The spectrum ranges from completely self-developed platforms to hybrid solutions and finally to completely purchased Software-as-a-Service (SaaS) solutions. The decision as to which solution is the right one depends on many different factors, such as budget, IT staff, investment costs, future maintenance costs as well as the overall business strategy. I can support you in the evaluation process to find the optimal solution for your company.

Problems of stability often happen when components aren’t properly decoupled. Individual component failures should have no impact on the overall system. The following approach is often implemented in the context of big data: Data input, processing, distribution and visualization should be independent process steps that must not have any impact on each other. A underlying system architecture and the implementation of interfaces between the process steps can support this behavior. I can help you with defining a decoupled architecture that supports the integration of separated interfaces that support stable processes.

One aspect that is often overlooked is the integration of governance and architecture. Governance and architecture must interlock so that they can be supported technically. If this does not happen, there is a risk that many processes will run much more slowly than would be technically possible. I can help you to align architecture and governance to prevent slow processes.

References are coming soon!

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