What most early-stage startups get wrong about their data stack (from 9 years in BI consulting)
Most founders I talk to think their data problem is a tool problem.
They're evaluating 5 BI tools. Debating Looker vs Power BI vs Metabase. Meanwhile, their underlying data is a mess.
Here's what I see most often across FinTech and SaaS clients:
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Reporting directly from the production database
Your ops team runs slow queries that time out during peak hours. You're reading stale data. One bad join takes down the app. I've seen this at companies doing $2M+ ARR. -
No single source of truth
Sales says the number is 4,200. Finance says 3,980. The CEO trusts neither and makes a gut call. That's a data warehouse problem, not a people problem. -
Building dashboards before cleaning the data
Beautiful charts. Wrong numbers. Leaders stop trusting reports entirely -- which is worse than having no BI at all.
The fix isn't always expensive. For most pre-Series A startups, a properly configured SQL Server + a staging layer + Power BI gets you 80% of what you need in 2-3 weeks.
I put together a free set of SQL Server diagnostic scripts that catch these issues early: https://growthwithshehroz.gumroad.com/l/psmqnx
What data challenges are you running into as you scale? Would love to hear what's tripping people up.
Yes, makes sense.
I can’t DM directly here on IH, so I sent you a LinkedIn connection request.
Accept it there and we can discuss Davoq properly around the infrastructure-trust positioning and whether it fits the direction you’re moving toward.
The core point is simple: if the business is moving from scripts/advisory into data infrastructure trust, the name has to stop signaling “helpful expert” and start signaling “serious infrastructure layer.”
That shift from "BI problem" to "infrastructure trust problem" is the exact inflection point I try to identify early in every engagement. When nobody trusts the numbers, no dashboard redesign will fix it — you need to rebuild the foundation first.
On the positioning angle, it's a real tension. The infrastructure framing is accurate for what the work actually is. For now my focus is helping startups get that operational data layer right before they layer dashboards on top — that's where the real leverage is pre-Series A.
If you're running into any of these patterns yourself, I have a free diagnostic script pack that helps surface the root cause quickly → https://growthwithshehroz.gumroad.com/l/psmqnx
Makes sense.
I think we’ve probably taken the public thread as far as it can go.
The Davoq fit is really about whether you want the brand to move from advisory/scripts into a more serious data infrastructure trust identity.
Here’s my LinkedIn so we can discuss it properly there:
https://www.linkedin.com/in/aryan-y-0163b0278/
No need to stretch it further here.
Appreciate the thoughtful framing, but I'm going to pass on the rebrand angle — the GrowthWithShehroz lane (practical SSIS/SSRS/Power BI for SMBs and freelancers, plus the small Gumroad library) is intentional, and the "data infrastructure trust identity" positioning would point at a different audience than the one I'm building for. Happy to keep the conversation public if there's anything specific from the post worth digging into — public threads tend to be more useful for the next person Googling the same question.
That makes sense.
If GrowthWithShehroz is intentionally built around practical SQL/BI education, SMB advisory, and the Gumroad library, then staying close to your personal brand is probably the right call.
The infrastructure-trust framing would point at a different market, more funded SaaS/data teams than freelancers or SMB operators.
Appreciate the clear answer. No need to force the Davoq angle if it does not match the audience you’re building for.
The interesting part is that once companies hit the “nobody trusts the numbers” phase, the problem usually stops being BI and becomes infrastructure trust.
Most early-stage teams think they need prettier dashboards.
What they actually need is a cleaner operational data layer with ownership and consistency built in from the start.
That’s also why a lot of “analytics” companies eventually outgrow descriptive names and consultant framing. The category starts moving closer to core infrastructure.
Something like Davoq.com would fit this direction much better long term than another analytics/BI-style positioning if you keep expanding deeper into the stack.
@aryan_sinh You've nailed it -- the work is infrastructure, the label just hasn't caught up. That gap between 'BI consulting' and 'data infrastructure trust' is exactly the conversation worth having pre-Series A, not post-Series B when the mess is already baked in. Staying in the GrowthWithShehroz lane for now, but the framing you've described is where the real leverage lives. For anyone in that 'nobody trusts the numbers' phase -- my free diagnostic scripts help identify where the trust broke down: https://growthwithshehroz.gumroad.com/l/psmqnx
100% — "infrastructure trust" is exactly the right framing. I've seen teams spend 3 months picking the right BI tool while their source tables have no primary keys, no documented ownership, and 4 different definitions of "active user." The dashboards look gorgeous. Nobody trusts them.
The shift I try to get clients to make early: stop asking "what dashboard do we need?" and start asking "who owns this number and how is it calculated?" That single question surfaces more data quality gaps than any tool audit.
On the positioning point — you're right that "analytics consultant" starts to feel limiting once you're rebuilding data contracts and governance frameworks. The work is infrastructure. The label just hasn't caught up.
If you're working through the SQL layer underneath all of this, I put together a query optimization handbook that gets into some of these patterns: https://gumroad.com/l/gwiow
Exactly — that line is the whole issue:
“The work is infrastructure. The label just hasn’t caught up.”
That’s usually where positioning starts capping the business.
If clients are buying trust in the operational data layer, then “analytics consultant” undersells what you’re actually solving.
Dashboards are the visible layer.
But the real value is making the underlying numbers believable enough for teams to act on.
That’s closer to data infrastructure trust than analytics.
If you keep moving deeper into contracts, ownership, and governance, the brand eventually has to carry that seriousness too.
Completely agree — "data infrastructure trust" is the category, not "analytics consulting." The governance and contracts work is where the real stickiness comes from, because once you own the data contracts layer, you're embedded in how the business runs. Changing that is expensive and disruptive, which means the relationship depth is fundamentally different from a dashboard project. I'm going to keep refining this framing. The brand has to carry that weight of infrastructure, not just output. Appreciate the continued thread — this is exactly the kind of positioning sharpening that's hard to get from just thinking about it solo. Free SQL diagnostic scripts if you ever need them for your own data stack work → https://growthwithshehroz.gumroad.com/l/psmqnx
That’s the right category.
Data infrastructure trust is much heavier than analytics consulting.
But if that’s the direction, the brand has to stop feeling like content, scripts, or advisory work.
Otherwise people keep reading the work as useful expertise instead of a system they can build operational trust around.
That’s where Davoq fits the layer better.
It doesn’t sound like BI.
It doesn’t sound like a handbook.
It sounds closer to infrastructure.
If you’re serious about moving from diagnostics and consulting into a more durable platform or infrastructure identity, that naming layer is worth pressure-testing seriously.
That Davoq framing is sharp — and you're right that the brand signal matters as much as the actual work. The diagnostic scripts and handbook currently feel like "tools" when the real value delivered is owning how a company's numbers behave across the stack.
The framing I keep coming back to: the scripts are proof-of-depth for clients who don't yet know they have a data trust problem. Once they see the gaps — suddenly the conversation shifts from "can you build me a dashboard?" to "we need the underlying layer right first." That's the consulting-to-infrastructure bridge that's hard to communicate upfront but becomes obvious after the first engagement.
Still working through how to make that visible before the first conversation. The positioning point you're making — infrastructure identity vs. content/advisory framing — is exactly the sharpening I need to do. Appreciate you pushing on it.
Free SQL diagnostic scripts if you ever want to run them on your own stack → https://growthwithshehroz.gumroad.com/l/psmqnx
That’s exactly the bridge.
The scripts pull people into “SQL help.”
But the real business is moving toward “data infrastructure trust.”
Very different signal.
Just to be transparent, I own Davoq.com.
I mentioned it because it fits this direction specifically, not randomly.
If you’re serious about moving beyond scripts and advisory into a stronger infrastructure identity, Davoq is worth discussing.
Appreciate the transparency on Davoq — that kind of disclosure builds more trust than most pitches do. The direction makes sense: once the conversation is about infrastructure, the relationship is fundamentally different from project-based work.
The bridge problem you're naming is real: scripts are the accessible entry point but they signal "tool provider" not "infrastructure partner." The conversation shift happens — but usually only after the first engagement surfaces something structural. Making that visible upfront is the hard part.
Worth a DM on Davoq. Genuinely curious about the naming layer approach.
If it's useful context for building out the practice side — there's a starter kit for productizing data advisory work here: https://growthwithshehroz.gumroad.com/l/cpfja
Appreciate that.
Yes, this is better handled in DM.
Davoq only makes sense if you’re serious about moving the identity from scripts/advisory into data infrastructure trust.
That’s the layer I think it fits.
Send me your LinkedIn or email and we can discuss it properly.
Appreciate it — send me a DM here on IH and we can pick it up properly. Happy to talk through the infrastructure framing and what that transition looks like in practice.
For context, I work mostly with funded FinTech and SaaS startups (US/UK/UAE) in the pre-Series A to Series B range — the exact stage where the consulting-to-infrastructure shift tends to happen. Would be a useful conversation.
Also leaving this here for anyone following the thread who's interviewing for SQL Server roles or needs to audit their own stack → free SQL Server interview Q&A I put together: https://growthwithshehroz.gumroad.com/l/vgiex