The Psychology of Data Transformations & Optimizing Multimodal AI Pipelines

Dear Data Enthusiasts,

Join us again on 29th of May at A1 to learn about the psychological implications on employees when transforming the data landscape of an organization. In addition, we will finally have a talk about the open source framework Metaxy and how it can help to cut costs of multimodal AI pipelines.

A big thanks goes to our co-organizers from the A1 Telekom and our sponsor Cloudera!

A Psychological Autopsy of a Data Transformation
Dávid Farkas
Five years ago, a small European university decided to build and implement a data strategy from scratch. Greenfield in the truest sense: data governance was an unheard term and in practice it meant local Excel files duplicated across inboxes; "the database" usually referred to whichever spreadsheet someone had emailed most recently. Over four years, we designed and rolled out new systems, established governance structures, hired a team, and delivered real wins. We also watched a significant portion of the work get undone in months once leadership changed.
This talk is a psychological autopsy of that transformation — what was planned, what worked, what quietly collapsed, and why. Universities are an unusually honest laboratory for studying data initiatives: decentralized power, competing stakeholder logics, weak formal hierarchies, and ambiguous success metrics make every human dysfunction that exists in corporate environments more visible.
Drawing on behavioural science and nearly five years leading this initiative, I'll walk through the recurring failure patterns I see across data and AI projects more broadly — algorithm aversion, NIH syndrome, the gap between executive sponsorship and operational ownership, and the under-recognised role of organisational identity in determining which systems survive a leadership change. The argument is not that technology doesn't matter — it's that the human substrate determines whether any of it sticks. Borrowing Kranzberg: technology is never neutral, and nei