What's the biggest challenge facing data teams today?

Ineffective BI tool? Doubts over data quality? Team bandwidth? Whatever it is, rest assured, you're not the only one. 

After conducting market research with a number of data professionals on their biggest frustrations, here are the four most common problems they mentioned. 

#1 "Business users aren't engaging with dashboards they ask for."

Most major BI tools are designed for data analysts and dashboarding rarely meets business users where they are.

Why it happens: Business users don’t usually engage with complex dashboards that lack a clear narrative or require effort to navigate. Business users think in terms of specific questions, not metrics. So, BI tools and dashboards rarely provide quick, actionable insights they want, without extra work. 

#2 "I really feel like we've become gatekeepers of data and insight."

Many data professionals feel reduced to bottlenecks. Other teams rely on them for every single data question, even simple or repetitive ones. 

Why it happens: As business users often can't easily self-serve through a BI tool, analysts are their only source of truth. Over time, this creates frustration on both sides: business users feel disconnected from data, while the analysts are overwhelmed.

#3 "I'm wasting days just clarifying simple requests."

Even basic data requests can spiral into days of follow-up emails, JIRA comments, and Slack threads. 

Why it happens: There’s a disconnect between the way business users ask questions and how data teams interpret them. Getting vague requests, leading to constant dashboard tweaks is a typical result. Even when an analyst finds time to build a new dashboard, the requestor's needs may have evolved - or worse, they’ve moved onto something else.

#4 "Our data is a mess." 

"Garbage in, garbage out" is a problem most data teams contend with, and new BI/AI enhancements don’t change underlying data quality. 

Why it happens: When data comes from multiple sources, or an org scales quickly, it's hard to keep all that data clean. Without consistent definitions or rigorous governance, most warehouses are far from perfect. The larger the org, the more inconsistent, duplicated or incomplete data you find. That said, even small amounts of good-quality data can have a big impact.

Your next step

These problems are long-standing, but they don't have to be permanent fixtures.

Just get in touch with our team here, we'd love to help.