Sustainable

Data platform

For headache-free data storage and data processing.
Terms such as Data Warehouse, Data Lake or Data Lakehouse should not affect you, we take care of the ideal solution for your company. No need to worry.

What challenges can we solve?

Data chaos & silos - no one knows where which data is located

Data is scattered across countless Excel spreadsheets, old systems and specialist departments. Everyone is working with a different version of the truth. The result? Errors, inconsistencies and endless meetings to find out which figures are correct.

Slow, manual processes - too much copy-paste, too little automation

Data has to be laboriously exported, transformed and prepared manually - often using copy-paste in Excel or self-made scripts. This takes time, is prone to errors and leads to frustration among employees.

Lack of real-time insights - decisions based on gut feeling

Many companies have data, but no fast and reliable analyses. Reports come too late, dashboards are outdated or inconsistent, and decisions are still made based on gut instinct.

Scaling problems - IT struggles with growing data volumes

What worked five years ago is now reaching its limits: Databases are overloaded, queries take forever and new requirements overwhelm the existing architecture. A modern, scalable solution is urgently needed.

The right architecture - whether data warehouse, data lake or lakehouse

Every company has different requirements for its data platform - but don't worry, you don't need to know whether a data warehouse, data lake, lakehouse or data hub is the right choice. We analyze your needs, evaluate the right architecture and implement a scalable solution that fits your company perfectly. No hype, no buzzwords - just a well thought-out and future-proof data strategy that really works.

Step by step

News on the topic of data platforms

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FAQ - Data platform for Swiss SMEs

What is a modern data platform - and what do you need it for?

A data platform is the technical backbone for analysis, reporting and automation. It collects, structures and links data from various sources - e.g. ERP, CRM, web or IoT. Modern platforms are often based on Azure, Databricks or Microsoft Fabric and are cloud-based, scalable and secure.

A complete platform usually includes: Data integration (ETL), data lake or warehouse, semantic layer, governance and front-end tools such as Power BI. We design architectures that suit the company - from simple solutions to scalable lakehouse models.

We start with an analysis phase: goals, data sources, use cases. This is followed by the target image design, selection of suitable technologies and implementation - step by step: proof of concept, MVP, rollout. BI & AI strategy, digitalization & automation

We work across all technologies. Depending on the scenario, we use Databricks (Lakehouse, Streaming), Azure (SQL, Synapse, Data Factory) or Microsoft Fabric (complete SaaS solution). We use Power BI for reporting.

A classic data warehouse is suitable for stable, structured analyses - such as financial reporting. The lakehouse model combines structured and semi-structured data (e.g. log files, JSON) and is ideal for machine learning, AI and streaming. Technologies such as Databricks support both.

Scalability, security, automation. Cloud solutions such as Azure or Fabric allow infrastructure to be used dynamically, backups to be managed automatically and authorizations to be controlled centrally. They reduce maintenance costs and increase agility.

GDPR compliance, hosting location and integration into existing on-prem systems are important. Many customers in Baden, Zurich and German-speaking Switzerland use hybrid models that combine Azure or Databricks with internal systems. We provide support with architecture, security and governance.

We integrate ERP, CRM or Excel data into the central platform via connectors, APIs or ETL processes. Tools such as Azure Data Factory, Power Query or Databricks Notebooks are used for this. The aim is: uniform data, a central model.

This depends on the complexity, technology and desired level of automation. For SMEs in Switzerland, we offer modular entry-level packages - e.g. MVP on Power BI + Azure. The investment usually pays for itself quickly thanks to improved transparency and more efficient processes. Data analytics & reporting

Yes, many customers start with a specific use case - such as a reporting solution with Power BI - and later expand to a complete platform. We support both selective projects and the gradual development of the platform. Support with tenders

Ready for transparent, data-driven decisions?

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