Data Quality: Myth of Perfection or Essential Standard?

"Garbage in, garbage out"—a phrase every data professional knows well.

IMPORTANT
Register for the event here: https://www.linkedin.com/events/dataquality-mythofperfectionore7274452059305787393/

Whether you're building dashboards, conducting analysis to drive decisions, or training machine learning models, data quality is key. This holds especially true when trying to leverage the power of GenAI.

But what practical strategies can help ensure data quality at scale?

On the flip side, is perfect data truly attainable?
How much time do we, as data professionals, spend resolving edge cases that may have minimal impact?
Where do we draw the line between precision and effort?
We'll unpack these questions with a panel of experienced data professionals, sharing diverse perspectives in different contexts, from startup to corporate.

Practicalities
🥤🥙Drinks & some food will be provided, so we can all survive the evening :)

📣 Meet Our Speakers 📣
Our speakers bring a wealth of experience, representing various fields—from engineering to analytics—and organizations of all sizes, from fast-growing scale-ups to large corporates:

Iryna Horova – Data Science Insights Manager (Product Analytics) @Catawiki
Arianne Leijenaar – Data Governance Expert
Rick Cobussen – Global Data & Insights Manager @FrieslandCampina
June Rodríguez – Engineering Manager (Payment Insights & Analytics) @Adyen
Romane Persch [Moderator] – Head of Data & Insights @Fastned

🔑 Key Topics We’ll Explore 🔑
✅Real-world examples illustrating the importance of data quality and its challenges
✅Practical ideas to manage data quality without overextending your resources (tooling, processes, etc.)
✅When "good enough" is the right choice
✅Why organization and culture matter, and how to drive change

💬 Why Attend? 💬
This session brings together professionals from various industries—including e-commerce, fintech, sustainable energy, and global corporates—offering diverse perspectives on data quality.

Whether you’re in Data Engineering, Data Analytics, or Machine Learning, you’ll hopefully walk away with actionable insights to implement in your organization!

We also aim to keep the audience small enough for the session to remain interactive, ensuring you have plenty of opportunities to connect with other professionals after the panel discussion.

🚨Save Your Spot Now!
Click [RSVP on LinkedIn] to secure your seat and join this hopefully thought-provoking conversation!

Please Note:
- Space is limited, and to ensure the discussion stays focused, we may not be able to accommodate everyone. If that’s the case, we’ll let you know in advance.
- You have to be registered on the event in order to attend

Register for the event here: https://www.linkedin.com/events/dataquality-mythofperfectionore7274452059305787393/