Data lands in Databricks from every system you own, the pipelines run fine, and still nobody can agree on how many customers the company has, whether two supplier records are the same company, or which product hierarchy the reports should be using.

In 45 minutes, element61 and Profisee look at where master data management fits into a Databricks platform, why AI makes the gap harder to ignore, and what a first project looks like if you want it live within a quarter.

Includes a live demo and 15 minutes of Q&A.

What you’ll take away

Agenda

Welcome and introductions.

Why element61 and Profisee are running this session together, and what you’ll get out of it.

Where AI projects run into master data.

What changes when an agent rather than an analyst consumes your data, what duplicate customers and competing product hierarchies actually cost, and the symptoms we see most often at clients.

MDM in a Databricks architecture.

Where mastering belongs in the medallion architecture, writing mastered data back to Delta tables, governance through Unity Catalog, and how MDM relates to the data quality and cataloguing tools you already run.

Live demo: Profisee on Databricks.

Modelling a customer domain, matching and survivorship, a steward resolving exceptions, mastered data landing in Delta, and governed master data made available to AI tooling.

Where to start.

Choosing a first domain, what a 90-day path looks like, what to measure, and the mistakes that make MDM programmes stall.

Q&A

Hosted by element61 – Privacy Statement

This event is free for element61 customers or organisations evaluating Analytics solutions. Registrations are only taken into account if made using a professional email address. Registrations of freelancers or other consultancy organisations will not be accepted unless with prior agreement from element61.

Note: The webinar will be conducted in English. A recording will be made available to registered participants after the event.