MANILA, Philippines (July 22) — Companies in healthcare, banking, energy, and retail are all rushing to use AI. However, they are quickly learning a simple lesson: AI can only give you good results if you feed it good data.
Exist Software Labs, Inc. teamed up with Microsoft and VST ECS Phils, Inc. to host an executive briefing called, “From Raw Data to Real Intelligence: How Microsoft Fabric Makes Your AI Strategy Real”. The discussion revolved around a major issue facing modern companies: getting data in order isn’t just a back-office chore anymore—it’s the single most important step to making sure tech investments actually pay off.
Jonas Lim, VP of Technology at Exist Software Labs, put it clearly during his session:
“AI is not a goal — it’s a means to one. The organizations that get real value from AI are those who start with a specific problem, not a technology. But wherever that problem leads you, it will always lead through the same place first: a trusted, unified data foundation.”
The first step to intelligence is acknowledging the systemic failure of the current, fragmented data landscape.
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The High Cost of Disconnected Data
No company intends to build data silos. They accumulate gradually as teams implement quick fixes for urgent problems. The result is a web of disconnected systems that silently drains productivity, wastes capital, and inflates the cost of doing business.
Addressing the cost of disconnected systems, Oliver Octoso, Product Support Engineer at Microsoft, pointed out the ultimate symptom of data sprawl:
“Nobody intentionally designs data silos. But when an enterprise runs over an average of 300 different applications, data stays trapped—and 66% of business data goes completely unused.”
The true cost of disconnected data reveals itself through four distinct areas of financial and operational leakage:
- Duplicated work & rework – Teams rebuild the same reports from exports that quietly disagree with each other
- Decisions left on hold – Strategy waits weeks for one complete, trustworthy picture of the business
- Wrong numbers, real fallout – Operating without a “single source of truth” leads to presenting contradictory metrics to board members, investors, or executives.
- Stalled AI & analytics – 77% say silos block real-time analytics; 83% say they stifle innovation. (IBM)
Oliver continues the discussion, presenting the case of “Houston Electrics.” Despite a 50-person data department and heavy investment in cloud providers, they were paralyzed by 364+ SaaS applications. Their Chief Data Officer (CDO) voiced a frustration common to many leaders: “I am the Chief Data Officer, and I don’t want to be the Chief Integration Officer.”
The human cost was just as high: data engineers spent every morning manually managing hundreds of messy pipelines, and it took three months to upskill new data scientists simply to navigate the intricacies of their fragmented platforms. This is not a “data problem”—it is an architectural failure.
The Real Barrier: Too Many Disconnected Tools
Trying to run a business by piecing together a dozen different apps and systems just doesn’t work anymore. This fragmented setup forces teams to pay a steep operational penalty—spending up to 80% of working hours just cleaning, fixing, and copying information instead of actually using it to drive business decisions.
Nico Lim, Data and AI Lead Engineer at Exist Software Labs, Inc., explained the internal toll this takes on workforce productivity:
“Most organizations don’t actually have a data problem—they have a platform problem. Stop drowning your IT and data teams in repetitive, manual data prep.
Instead of spending hours pulling and cleaning reports every single quarter, put that effort into building an automated platform that frees your team to focus on core operations.”
This disconnected setup creates another major risk: unreliable AI.
If enterprise systems are scattered and numbers aren’t connected in one reliable place, AI tools will simply fill in the blanks with false information—leaving decision-makers with inaccurate answers they can’t trust.
The Path Forward: A Practical Plan to Get AI-Ready
Moving from messy, raw information to real business intelligence doesn’t happen overnight—it’s about building a strong data foundation. By bringing your tools, security, and costs into one simple platform, Microsoft Fabric gives a clear path to turn AI into a reliable, profitable investment.
Likewise, upgrading systems doesn’t mean throwing away everything you already have. Microsoft Fabric is built to work alongside your current tools, allowing you to transition smoothly using a simple four-step process:
- Find the Bottleneck. Pick one major business problem where scattered information is slowing your team down.
- Start Small. Set up a quick trial project for that specific problem. In about 4 to 8 weeks, you will see clear, measurable proof of how much smoother things can run.
- Expand Success. Apply what worked to other teams and set up simple guidelines to keep your information organized across the company.
- Modernize. Slowly move off your old tools at a pace that makes sense for your budget and operations.
Need support or more information? Exist is here to help.
Whether you’re mapping your first data use case or ready to run a Proof of Concept, our team can guide you from assessment to activation — at a pace that works for your organization.
Exist Software Labs is a Microsoft Solutions Partner with deep expertise in data, analytics, and AI-readiness across Philippine and foreign enterprise clients.
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