When to Hire a Data Analyst vs. Outsource Data Infrastructure
A practical framework for mid-sized companies deciding between building in-house data teams or outsourcing data infrastructure.
Practical guidance on data strategy, infrastructure decisions, and building reliable reporting for mid-sized companies.
A practical framework for mid-sized companies deciding between building in-house data teams or outsourcing data infrastructure.
Most companies build data infrastructure reactively—responding to pain points as they arise. Here's why planning first saves you six figures and months of wasted effort.
You hired someone, bought the tools, built the dashboards. Six months later, nobody's using them. Here's why—and what actually works.
The hidden cost of hiring for analytics when you actually need infrastructure—and what to do about it.
Some companies sell products. Others sell products and data patterns. Understanding which you are changes everything about how you should invest in data infrastructure.
Waiting for clean data before building infrastructure is like waiting for a perfect day to start exercising; it's never coming. Here's what actually works.
When you can't automate everything at once, here's how to choose which department to start with; and why the squeaky wheel strategy often works.
Why most operational dashboards fail within 3 months; and how to build ones your team will rely on every day.
How to recognize when manual reporting has become a liability; and what to do about it before something breaks.
A financial framework for planning data infrastructure investments that pay for themselves; without over-building or under-delivering.
A practical self-assessment framework to understand your current data capabilities and plan your next move without over-investing.
Let's talk about building a reliable data foundation for your company.
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