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"Overall, the NPrinting workshop was excellent. We particularly liked that we could test directly within our own systems, using both live and prepared data."
Controlling & Reporting, MediaMarktSaturn
"inics' strategic guidance was essential in fully realizing our business intelligence potential. This enabled us to optimize previously overlooked processes and make better decisions aligned with our corporate goals, leading to significant monetary and qualitative improvements."
Stefan Schnarr, BI/CRM Team Leader - Adler Modemärkte
"The customized workshops with inics quickly empowered us to independently and successfully work on our BI topics. Their practical support allowed us to confidently master complex tasks."
Axel Meissner, Head of Controlling, perma-tec GmbH & Co. KG
„Thanks to the expertise and dedicated support from inics, our BI environment has significantly enhanced, becoming highly stable, scalable, and reliable.“
Christian Zander, Head of Reporting & Data Analytics, KiK
„The partnership with inics transformed our BI landscape, significantly reducing costs and establishing an innovative platform for future digital and AI initiatives. We see inics as strategic digital evangelists.“
Luka Bebensee, Operations Partner - Head of Quantoo/TMG
"inics proved their capability to successfully take over BI projects from other providers. Thanks to their extensive experience and competence, our Qlik project was completed successfully, to everyone's satisfaction."
Nico Alf, Team lead international Controlling and Foundation Management, Zoological Society Frankfurt
Careers at inics
We are continuously seeking interns, student employees, and data enthusiasts to join our growing team. Are you excited about the fast-paced, evolving world of data?
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Insights from the inics Blog
Stay up to date with our knowledge portal! Discover new articles regularly on the latest developments in data analysis, business intelligence, and current industry trends.
From Reporting to Decision Support - Why adaptive orientation matters when KPI autopilot fails
Too often, it was treated as if enough data, enough dashboards, and enough automation would eventually make decisions almost self-executing. That was always too simplistic. But once you stop confusing data-driven work with decision automation, the real question becomes much more practical: "What actually helps an organisation make better decisions when the old reading model starts to weaken?"
Data-Driven Decision Making: What It Really Means When the Environment Stops Behaving
Part 1: Why “data-driven” was often mistaken for decision automation, and why the real challenge is deciding whether your current signals still capture enough of reality to guide action.
Data Mesh, Data Meh? Why Many Companies Need to Reassess Their BI- and Data Organization
A few years ago, Data Mesh was, for many companies, above all a compelling target vision. More ownership in the domains, fewer central bottlenecks, more product thinking, more scalability. On strategy slides, it sounded modern, ambitious, and long overdue.
AI Use Case Inventory and Governance - Portfolio, Roles, Obligations
Part 3/3 concludes the series with the question that, in practice, often needs to be answered first:
Traceability by Design: Auditability Is Architecture, Not Documentation
Part 2/3 of the EU AI Act Series In Part 1, we focused on data quality. Part 2 builds on that. Because even with good data, the same question almost always arises in practice:
EU AI Act Art. 10: Data Quality That Withstands Audits
What data engineering must deliver before the high-risk rules take effect (Part 1/3). In many organizations, data quality was long treated as a hygiene topic: important, but rarely decisive. With the introduction of the High-Risk rules, data quality becomes verifiable. It must be measurable, controllable, and evidentially demonstrable in operations.