Treating data as a product
Find the best data team structure for your organization
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Data is the most important asset in the organization.
The business world is witnessing the rise of the data team as data has become recognized as a valuable business asset.
In this guide we explore examples of data team structures including a centralized team, a distributed model and a structure of multiple data teams.
Download the eBook to discover:
- The challenges of working in data in 2021
- A guide to data team structures with examples
- Breaking down communication barriers with a universal language
- Reducing data downtime with data observability
- How data storytelling can make your insights more effective
“We would not have achieved our current level of self-serve data without Snowplow. It has enabled us to democratize our data culture, significantly improving our analytics coverage and deepening our insights.”
Daniel Huang, Data Engineer at Strava
It’s an exciting time to be working in data. The opportunity for data teams to make an impact is huge. They have more tools at their disposal, with exciting technology hitting the market each day. But it’s not all roses.
Building and managing a modern data capability is a tremendous challenge. Aside from the technology involved, it requires working closely with technologists with a broad range of skill sets. It means working with (i.e. winning over) internal teams and stakeholders and educating them around the value of data.
Download the eBook to discover how you can better communicate the value of data in your organization.