Ah, conducting successful data platform evaluation (POVs)! It’s where dreams of data prowess either take flight or faceplant into the conference room coffee table. But fear not, fellow CTOs, because getting it right is less about luck and more about method. If you’re gearing up to decide whether Snowflake or Google BigQuery—or any big data platform player—deserves a slice of your IT budget, then strap in. We’ve got a data platform evaluation blueprint that’s more outcome-focused than caffeine on a Monday morning.
1. Set Your Scene with a Stellar Analytics Use Case
Start by defining a use case that screams relevance. It should combine at least two distinct data sources to really test the DATA INTEGRATION muscles of your prospective platforms. Are we talking sales data mingling with operations stats? Perfect. Write down what you need in clear, unambiguous language. Remember, clarity at this stage is the difference between a roadmap and a wild goose chase.
2. Choose Your Platform Evaluation Dance Partner Wisely
Now, decide who’s going to help you put this puzzle together. You can go solo and rely on your in-house talents or dance with a specialist analytics partner like Claudy (hey, that’s us!). Either way, sketch out a project timeline that doesn’t stretch beyond four weeks—speed is your ally.
3. The Tailored Platform Evaluation Matrix: Measure What Matters
Don’t drown in data points. Instead, create a tailored evaluation matrix. Pick 10 key criteria that align with your long-term goals. How does the platform handle real-time analytics? What’s the deal with scalability? Assign weights to these criteria based on your priorities. This matrix isn’t just a tool; it’s your compass. If you need inspiration, check out this evaluation matrix, created by Datateer and the Chartio Community. It is way too granular and it doesn’t contain weights on each criteria. But it gives you some ideas as to which topics you’d like to focus on.
4. Dive Into the Use Case Implementation
Roll up those sleeves and implement your use case. Adopt a customer-centric approach from the get-go. Why? Because the end-users of this data are your best critics. Gather their feedback diligently and score each platform on your matrix from 1 to 5. No mercy!
5. The Grand Finale: Summarise and Decide
With all the data in, summarise the results. Craft a compelling business case that weighs long-term benefits against costs. This is your ammo for winning over the management team. Show them the numbers, dazzle them with insights, and make that informed long-term investment decision.
Bonus Tip: Lean on Your Vendors
Remember, your platform vendors and service partners are more than just service providers; they’re potential partners in your data journey who can help you leapfrog the competition. Use their expertise extensively. After all, reinventing the wheel is strictly for hobbyists, not savvy CTOs aiming for the next business breakthrough.
The Takeaway: It’s All in the Execution
In summary, a successful POV isn’t just about planning—it’s execution that turns data potentials into palpable wins. Stick to this five-step approach, and you’ll base your investment decision on data-driven insights, not just gut feelings. Now, go forth and conquer those data platforms, and maybe—just maybe—turn that conference room coffee spill into a celebratory toast. Cheers to data victories!
👍 Found this guide helpful? Share it with someone who could use a clear path to conducting their own POVs. Trust me; they’ll thank you later.
If you’re already ahead, looking to maximise the value of your data platform, check out our blog post about How to Realise Stronger Returns on Data With Embedded Analytics.
