Beyond the Silo: Why fragmented data is holding back Indian enterprises

As India celebrates Technology Day, a reminder of the country’s achievements in digital innovation, the focus naturally shifts to the future of technology in driving business transformation. However, as the nation celebrates progress, many enterprises are grappling with a critical issue that could hinder their digital aspirations: fragmented data.

In India’s fast-digitising economy, data is abundant, but unified data is still elusive. Across sectors, from banking, financial services and insurance (BFSI) to manufacturing and media, enterprises are contending with a growing problem: fragmentation. Many large organisations today manage a complex mix of data systems, often spanning across different platforms, applications, and departments. As a result, integration challenges have become a major barrier for companies looking to streamline their analytics capabilities. This fragmentation can lead to disconnected insights, delayed decision-making, and a lack of trust in Artificial Intelligence (AI) models, which struggle to deliver accurate and consistent results when data isn’t unified or properly integrated. 

The Scope of Fragmentation

It’s a problem that goes far beyond IT. "One of the first stumbling blocks we see when implementing analytics platforms is the sheer sprawl of legacy and siloed systems,” said Rakesh Jayaprakash, product manager at ManageEngine. “Data may exist in abundance, but access is uneven, and context is missing. You can't drive intelligence if every team is operating on a different version of the truth."

Sudhan Rangarajan, GVP — Engineering at Publicis Sapient, emphasises, said, “As organisations accelerate their digital transformation, data fragmentation has become one of the most pressing challenges.” With data spread across legacy systems, cloud platforms, SaaS apps, and siloed business units, he stressed, “Creating a unified, scalable data ecosystem is critical.” This complexity includes scaling storage, compute, and activation, ensuring governance across ownership and compliance, managing data quality, defining success metrics, driving innovation, and fostering high-performing, cross-functional teams.

Fragmentation’s Growing Impact on Business

This fragmentation creates not just inefficiencies, but vulnerabilities. A McKinsey report found that 60% of failed data transformation initiatives globally stem from issues around governance and ownership, not technology itself. In India, this is exacerbated by rapid cloud adoption layered over existing on-prem systems.

In a media conglomerate overseeing multiple business divisions, even something as simple as consolidating travel and expenses across different units would take weeks, according to Girish Pai, SVP and Global Head of Data & AI at Hexaware. "There was no unified data source," he explained. "Finance had one figure, HR had another, and the CEO’s dashboard showed something completely different."

"Fragmented data also increases the risk of security, governance, and compliance issues. It becomes more difficult to detect breaches or ensure compliance with regulations like GDPR and DPDP. Without centralised governance, organisations are exposed to significant risks," said Srividya Kannan, Founder and CEO of Avaali.

Modern Data Architectures: The New Hope?

In response, enterprises are experimenting with modern data architectures, lakehouses, fabrics, and data meshes among them. Each promises to streamline access, increase observability, and scale insights without duplication. But none are silver bullets. “These models only work when supported by organizational alignment,” said Anil Allewar, Senior Director of Digital Transformation at Altimetrik. “We’ve seen companies invest millions into platforms like Snowflake or Collibra, but still fail because their teams don’t understand who owns the data or what quality standards to enforce.”

The Rising Compliance Pressure

The rising tide of data privacy regulation is raising the stakes. With India’s Digital Personal Data Protection (DPDP) Act now in force, companies can no longer afford the ambiguity of unclear lineage or scattered access control. As data systems grow more complex, organisations without robust observability strategies are increasingly vulnerable to compliance gaps and reputational damage. The absence of end-to-end data visibility can leave businesses exposed, particularly in sectors where trust, transparency, and regulatory scrutiny are paramount.

Creating a Data-Centric Culture

The shift, experts agree, must be cultural as much as technical. “Data is not just an asset; it’s a shared language,” said Clarence Rozario, Director of Product Management, Zoho BI Analytics Platform. He further said, “When we onboard new employees, we don’t just teach them our products — we teach them our data definitions, our metrics logic. Because that’s where alignment starts.”

Ultimately, solving fragmentation isn’t about chasing the newest tool. It’s about creating a consistent narrative around data, who owns it, who defines it, and who’s accountable for its quality. For Indian enterprises racing to embed AI across operations, that cohesion could be the difference between transformation and turbulence.