top of page

Zuma's Data Meet-up.

Scout24 X ZUMA - Berlin Meetup (4).png

How it went.

What an evening! Working alongside Scout24, we put together our third Data meet-up and this time we explored Data Products. Hot topic right now as our partners turn to us for business impact from their Data. So how did it go? 

Zuma Intro.

Matt got us started introducing Zuma and the work we do, for those who did not already know. Highlighting our future vision for recruitment in Tech and Data in Germany. 

We prioritise community and connection building because we understand that this is where growth and innovation play!

11A3B4BB-958E-47B8-A698-5E05F8B913A5_1_201_a.jpeg
Rieke in action.jpeg

Scout24's Presentation.

 

Rieke Ostues, Head of Data Infrastructure & AI, kicked-off the evening's technical topics by showcasing what Scout has been up to!

Giving great insight into Scout24's view of data products, and how her teams are addressing the challenges of Building Winning Data Products.

The Data Leadership Panel.

  • Eva Schreyer - Head of Data & Analytics (Neugelb Studios)

  • Rieke Osthues - Head of Data Tech & AI (Scout24)

  • Elvira Bekyrova - Engineering Manager, Data (Parloa)

Our expert data leaders, Elvira, Eva, and Rieke, then shared their valuable insights and experiences. They discussed the challenges they faced, the lessons they learned, and the outcomes of their data product journeys. 

And, they shared some advice about how data team members can contribute to the Wins too.

55A3D5C9-5821-4D38-BA70-E7118A813335_1_201_a.heic
BC357A68-BD66-4AB5-8C22-B31AAE8E31F9_1_201_a.heic

Workshops.

Our biggest satisfaction was seeing the attendees collaborating and debating in teams to produce some stunning interpretations of "What is data product?" 

It was great to have seen all of you data enthusiasts connecting, sharing, and socializing.


 

From gathering some great Data minds in one place we figured out the keys to Building Winning Data Products:

​​

  • Discoverability: Let's make it a no-brainer to understand and find, for our users

  • Accessibility: No tech wizardry required! Everyone should be able to jump in and get started

  • Reliability: We're talking about consistent, trustable, and accurate data

  • Value: It has to deliver the goods! Show us the money (or at least some measurable results)

  • Ownership: Always we need to be clear about who's in charge of 'keeping the lights on', making improvements, and rolling out newer versions

  • Tech-Agnostic: This tool is a chameleon! It'll fit right in with whatever you're working with

  • Interoperability: It can be integrated with other systems and data sources.
     

Our more detailed breakdown.

Zuma Summary:
Building Winning Data Products
.

We took some useful notes too!

What helps to form the Building Blocks of Winning Data Products? Data Mesh!


We came to define a data product as a valuable asset that is discoverable, accessible, reliable, and interoperable. It should have clear ownership, be technology-agnostic, and provide tangible benefits to more than one stakeholder group.

Essential Elements for Success:

  • Usability: Tailored to the needs of different stakeholders.

  • Impact: Measurable positive effects on business metrics.

  • Cost-Benefit Analysis: Justified by the value it provides.

  • Continuous Updates: Regularly maintained and updated to reflect changing data and business needs.

  • Real Data Foundation: Based on actual data sets, not hypothetical scenarios.

We recognise that it is only data teams that are 'data-driven', but businesses and tech teams are already on this path. And data people can follow similar processes as development teams in building their 'microservices', as long as we stay agile and deliver to the real business needs.


Challenges  vs Best Practices:


Varied Definitions: Companies have different interpretations of data products.
Learning from Experiences: We're failing, learning, and winning as we build more! 
Maturity Differences: Companies across Berlin are at very different stages of data product maturity.
Robust Infrastructure: a cohesive and established Data infrastructure is essential for building effective products.
Stakeholder Involvement: Collaboration with both data people and business stakeholders is crucial to understanding and fulfilling the needs.
Data Literacy: It is both the challenge and the goal of building data products. We need to democratise to help us build, and we need to build to help us democratise.


We learned that by understanding the key characteristics, the elements for success, and challenges, organizations have the best chance of successfully Building Winning Data Products that drive business impact and improve decision-making. So, for you data enthusiasts out there, seek to help your customers by educating them through collaboration empathy, and clear project goals. 

See you next time!

Get notified about our next Data Meet-Up.

SignUpForm

Keep updated about the next Data Meet-up

bottom of page