I’ll spare you the anticipation. The data team. That’s your biggest team, no matter your industry or line of business.

But wait, just who is on it? Well, if you work with data, you are. And anyone who should work with data, they’re on it. This means: IT, data stewards and curators, executives (hopefully), engineering, product, customer success, marketing, sales… you get the point. The reality is that everyone in your organization needs data. And if they can’t get it, understand it, or use it, they’re falling behind.

We’ve talked before about how technology and people need to work together. It’s time to focus on shaping your solution: make it people-first. Bring them together, collaborate effectively, and increase understanding.

Technology’s role

Technology's key function can be summed up in one word: workflow

Not only for IT and data engineers who need an easier way to connect data sources. That's important, but only a step.

Instead, think about how the work of your engineers links with stewardship and consumption. Loading the data is a useless exercise if nobody uses it. It’s a tree falling in the woods, to borrow a saying. The barriers and difficulties in accessing and working with data inherently discourage usage, however well intentioned. 

Many governance solutions today are control-oriented and centralized from the top. According to Gartner, this is an outdated approach because it fails to take into account diverse business needs.

Your business is dynamic, and strategies evolve over time; your solution should complement this reality. It needs to be resilient to solve many evolving business problems in parallel.

What does this look like, exactly? These are some key capabilities to keep an eye out for:

Think of your people 

Technology can make data-driven people much more powerful. Today, we’re producing tons of data but consuming a mere fraction of it. And so we still have a large gap between data producers (data engineers, data stewards, etc.) and data consumers (analysts, data scientists, subject matter experts, etc). 

Data Product Managers and Knowledge Scientists can be the bridge. They connect the contextual business understanding together with raw technical information. With that combination, their subjective analysis enables entire organizations to understand data better.

A data product team and the role of the knowledge scientist takes on responsibilities such as:

Most organizations today have a dedicated, technical-focused data team, but this isn't enough. It's one thing to have a deep understanding of the raw information. It's another to extract knowledge by bridging the business-technical gap.

Imagine if everyone in your organization had usable and understandable data to enrich their projects. That's what knowledge does. And you know this!