Business Intelligence and Analytics

This hub collects the technical write-ups our engineers use when they’re picking a BI stack, tuning dashboard performance, or explaining data to a non-technical stakeholder. The focus is practical: how tools like Tableau and Power BI actually behave under load, what chart types communicate cleanly, and where data visualization choices help or hurt a decision. It’s written for engineering leaders who need to justify a platform choice, not just admire one.

Some pieces work as reference material years after publication. Our guide to diagnosing Tableau performance bottlenecks walks through the same triage steps we use on client dashboards that have slowed to a crawl. A companion piece on pairing Power BI with AI features covers what’s genuinely useful versus what’s still marketing. If you’re earlier in the decision, the comparison of tools for data-driven decisions is a reasonable starting point before you commit budget to any single platform.

When the question moves from which tool to who builds and maintains this, that’s usually when teams bring in outside help. We support that work directly through our business intelligence services, and for teams weighing platform migrations or governance questions, our Data Engineering and Governance articles cover the layer underneath the dashboards. For dedicated build-outs, our BI development services team typically starts with the same audit questions these articles raise.