Your company has more data than ever, and it’s scattered. Marketing’s buried in giant spreadsheets, sales live in the CRM, ops have their own dashboards—and no one’s working from the same playbook.
So when someone asks a simple question, “How did our business perform last quarter?”, you get five different answers. Reports clash. Numbers don’t line up. And nobody’s sure which version to trust.
That’s the real cost of data silos: they quietly keep you guessing, delay decisions, and erode trust when you need it most.
The good news? You don’t have to stay stuck. Here’s how to break down your data silos for good.
Table of contents:
Data silos are isolated pockets of information that prevent data sharing between different departments, teams, and business units.
The result?
Everyone ends up working with their own version of the truth. Instead of sharing knowledge and collaborating, your team wastes hours redoing work, questioning numbers, and missing the bigger picture that could help you make smarter moves.
Think about it: Imagine your data science team is training a fraud detection model using only payment data. But contextual information like login activity, IP addresses, or device fingerprints is in separate systems managed by other teams.
With that blind spot, you’re more likely to get weaker predictions, more false positives, and a bigger risk of fraud slipping through the cracks.
Fragmented data
Even with the best tools, fragmentation creeps in when systems aren’t designed to connect. What starts as simple tooling decisions—like finance preferring spreadsheets and customer success leaning on CRM reports—quickly turns into a disconnected data landscape where no one sees the full picture.
⛏️Fix: Establish a single, real-time source of truth, so everyone works from the same reliable numbers.
Take the case of Publicis Sport & Entertainment. Analysts spent thousands of hours on manual reporting, slowing down time-to-insight, while data scattered across 300+ broadcasters made analysis fragmented and time-consuming.
By modernizing their data stack with ThoughtSpot, the company was able to put insights directly into the hands of consultants and clients. This helped accelerate client onboarding 90% faster, from 6 months to 2-3 weeks.
IT complexity
Chances are, you’re likely relying on dozens of systems, apps, and tools, each with its own quirks and rules. Without a clear plan to keep everything connected, all those moving parts turn into a tangled web of overlapping databases, mismatched integrations, and fragile links.
Even simple tweaks like renaming a field or updating a pipeline can quietly break dashboards or sever syncs between systems without anyone noticing.
⛏️Fix: Audit your tech stack regularly. Spot redundant tools, outdated pipelines, and simplify what you can so your data stays connected.
Legacy data analytics systems
Traditional BI tools often come with clunky interfaces that require complex SQL or Python queries just to get basic answers. That puts everyday insights out of reach for most of your team, forcing them to rely on IT teams for every new report.
This creates hidden data silos: pockets of insights locked away with specialists, while everyone else works with stale dashboards, manual exports, and endless workarounds.
⛏️Fix: Move to modern analytics tools that keep your data fresh, accessible, and easy for anyone to use.
With ThoughtSpot’s AI-powered dashboards, data refreshes automatically, so you’re never stuck with stale numbers. And you don’t need to be a data wizard to use it. Anyone can click, filter, and dig into the details to find answers fast.
No clear governance controls
When it’s unclear who owns what, how data should flow, or who gets access, your teams create their own workarounds. That means multiple versions of the same data, inconsistent definitions, and confusion over which numbers to trust.
⛏️Fix: Build a strong data governance framework. Define clear ownership and set consistent data standards, so everyone knows who can see and change what.
Lack of data literacy
If your team doesn’t understand why clean, connected data matters or how to manage it, they’ll naturally fall back into old ways of working. For example, they might save their own copies of spreadsheets on their laptops or build manual workarounds instead of sharing updates in a central system.
Over time, this creates multiple versions of the same numbers with inconsistent definitions and a lot of duplicated effort.
⛏️Fix: Make data literacy a priority. Invest in training and documentation, creating simple guides so everyone knows how to enter, store, and share data the right way.
Build explainability into your data tools
If you don’t know where a number comes from or how it’s calculated, it’s only natural to question it. And that’s exactly how hidden silos creep in.
Trust comes from transparency. Your analytics tools should make it easy for people to see which data sources were used, how queries were interpreted, and where any assumptions were made. When everyone can trace the path from raw data to final metric, they trust what they see, and they can act faster with confidence.
Reward a data-sharing culture
Technology can only take you so far. Silos often stick around because people treat data as power to protect, not a value to share.
Set the tone that data is a company-wide asset, not a bargaining chip. Celebrate teams that make their data easy to access, reuse, and build on. When people see that openness is valued and rewarded, they’re far less likely to keep valuable insights locked away.
Standardize your data
Standardization is the backbone of trust and collaboration. If every team defines a metric differently, like “active user” or “qualified lead”, you’ll end up with multiple versions of the same KPI. That’s exactly how conflicting reports and one-off spreadsheets pop up and spread confusion.
Create clear, company-wide definitions, naming conventions, and data quality standards. Document them in an accessible data dictionary so everyone can stay aligned.
Tackle the big blockers first
Trying to fix every disconnect at once can stall momentum. Focus on the silos that create the most friction: the duplicated customer records that waste analyst hours, the legacy systems no one trusts, or the manual data processing that slow down critical decisions.
By solving the high-impact pain points first, you show real progress fast. It’s a strategic move that frees up time and budget, without disrupting your team’s workflow.
The hidden costs of data silos
Drains your team’s efficiency
Research shows that on average, employees spend 12 hours every week just chasing down data.
Instead of pulling up one clear report, you’re jumping between systems, patching together spreadsheets, or waiting on your analyst to send an update. By the time the numbers land in your inbox, they’re probably already out of date.
Over time, this lost productivity snowballs into missed deadlines, burned-out employees, and hidden operational costs that drain your bottom line.
This is why industry leaders trust ThoughtSpot. With all your data in one place, and Spotter, your AI Analyst, ready with answers in seconds, you can stay focused on what really matters. No more wasting time hunting down numbers across endless dashboards and spreadsheets.
Breaks customer trust
Data silos don’t just shake your confidence; they break your customers’ trust too.
Say a customer updates their contact info in your app, but the change never reaches the billing team. An invoice is sent to the wrong address, another email goes to an outdated account, and now the customer has to explain the same issue over and over just to get it fixed.
That kind of disconnected experience chips away at their trust in your business, one interaction at a time. Ultimately, if you can’t trust your data, you can’t expect anyone else to trust your business either.
Creates compliance gaps
With data silos, staying compliant is ten times harder than it should be.
Without a single, consistent policy for protecting sensitive data, you’re forced to create controls for each system, tool, and spreadsheet you use. That means more manual work, higher costs, and more chances for something important to slip through the cracks.
And when you can’t see all your data in one place, every audit feels like a last-minute fire drill, putting you at risk of penalties and fines.
Turn data silos Into insights everyone can trust
Breaking down data is only half the battle; making it usable for everyone is where the real win lies.
ThoughtSpot’s Agentic Analytics Platform gives every user access to governed, up-to-date data they can explore without barriers. With Spotter, your AI Analyst, you can simply ask a question in natural language like “What’s driving churn in this region?” or “Which product line is underperforming?” and get instant insights within seconds.
Instead of digging through stale dashboards or waiting days for a new report, your team can go from question to clarity in moments.
See how Spotter helps teams break silos—and move from scattered insights to shared action. Schedule a demo today.
How can data silos affect decision making?
When your data is scattered across different silos, you're essentially making decisions with only part of the story. It's like trying to solve a puzzle with half the pieces missing. You might think you're making smart choices, but you're actually working with incomplete or inaccurate information. This can lead to missed opportunities, poor investments, or strategies that just don't work.
Why do data silos occur?
Data silos don't just happen overnight, they're usually the result of how organizations naturally evolve over time. When departments operate independently with their own budgets, goals, and leadership, they tend to build walls around their data. The result? Information gets trapped in these isolated pockets, making it difficult for you to get a complete view of your business.
What is an example of a data silo?
Imagine your social media team is using specific tools to track customer engagement and feedback. They gather lots of valuable insights, but the product team only gets occasional reports, meaning they’re missing out on critical signals that could help improve products. This is a classic example of how data silos can creep into every corner of your business.
What are some strategies to break down data silos?
Breaking down data silos requires a multi-faceted approach that combines technology, culture, and processes. When you combine the right technology with the right mindset and clear processes, you can turn those isolated data silos into a unified, accessible information ecosystem that empowers better decision-making across your entire organization.
