Instead of planning your data capability based on where you are right now, begin with where you want to be. Creating a data catalogue driven roadmap will set your teams up for long-term success and avoid unnecessary migration projects or ‘development pauses’ to rework the backend.
Why This approach? By establishing an architecture early that can handle your full spectrum of possible use cases, you’ll reduce rework down the line. This strategy allows you to build a flexible, scalable system that grows with your needs. Moreover, it provides a clear vision for stakeholders, aligns teams around common goals, and ensures that your data initiatives are driven by objectives not ad-hoc requests.
Here’s how to create a data catalogue driven roadmap that’ll get you there.
1. Envision Your Ideal Data Catalogue
First things first, picture your perfect data catalogue years from now. What does it look like?
Consider:
What data assets and products are included?
How are definitions and functional structures organised?
What are your discoverability goals?
How will access controls work?
What does your data lineage look like?
Don’t limit your consideration to delivery just via traditional dashboards. Think about external data sharing, machine learning models, real-time streaming dashboards, and more.
You might be wondering, “How far into the future should I plan?” While it’s impossible to predict every future need, aim to look at least 3–5 years ahead. This timeframe allows you to anticipate major shifts in your industry or organisation while remaining grounded in realistic planning.
Another common question is, “What if we don’t know all our future use cases?” That’s okay! The goal isn’t to predict every possible scenario, but to create a flexible framework that can accommodate a wide range of potential needs. Focus on building adaptability into your system rather than trying to anticipate every specific use case.
2. Plan for the Full Lifecycle
Everything you build today will be legacy one day in the future. Consider:
How will you handle version control?
What’s your plan for decommissioning assets and definitions?
How will you clearly share assets in draft, MVP, and future states, and communicate that clearly to your users?
It’s common to worry about maintaining data quality throughout this process. Remember, your data catalogue should include mechanisms for data quality assurance, including data profiling, validation rules, and regular audits. These should be built into your planning from the start, not added as an afterthought.
3. Work Backwards
Now that you’ve got your end goal, it’s time to break it down. What components do you need to make this vision a reality? This is where your roadmap starts to take shape.
Start by identifying the major building blocks of your ideal data catalogue. These might include data ingestion processes, metadata management systems, data governance frameworks, and user interface designs. Then, for each of these components, list out the specific features or capabilities you’ll need.
4. Prioritise and Categorise
Look at your list of components and start prioritising:
- Foundational elements are your must-haves, like platform architecture and governance controls.- Quick wins give you immediate value.- Strategic initiatives are important but might take more time and resources.
This prioritisation becomes your product roadmap.
So how do you balance quick wins with long-term strategic goals? The key is to create a roadmap that delivers value at regular intervals while steadily progressing towards your larger objectives. Even better if your quick wins can accumulate together into a benefit that is larger than the sum of its parts. Aim to intersperse your quick wins amongst your more complex, strategic projects to maintain momentum and stakeholder buy-in.
Remember, this isn’t a one-and-done deal. Revisit and adjust your roadmap and ideal future state catalogue regularly as you learn and improve.
Embrace a Data-First Mindset
This approach promotes cross-functional collaboration, breaks down data silos, and creates a shared vision for data management across your organisation.
Remember that the true value of this exercise lies not just in the roadmap itself, but in the cultural shift it represents. Encourage your teams to think critically about how data can drive decision-making and innovation in every aspect of your business.
As your data continues to grow in importance, organisations that have embraced this data-first mindset will be well-positioned to thrive. They’ll be able to adapt more quickly to new technologies, extract more value from their data assets, and make more informed, data-driven decisions.
So, don’t just create a roadmap — use this process as a catalyst for transforming how your organisation thinks about and uses data.