Inside the Systems Powering the World's Data Decisions

Modern institutions face mounting challenges as their information is scattered across countless platforms, formats, and record-keeping systems. Duplicate entries, mismatched structures, and inconsistent updates often cause basic facts to drift out of sync. The result is an information landscape that is difficult to trust and even harder to act on.

Software engineer Nadira Pranatio believes these issues reveal a deeper structural problem in how organisations treat their data. Armed with a computer science degree from Northwestern University, she has worked in environments where high-stakes decisions depend on coherent, reliable information.

Today she serves as an engineer at a major data-infrastructure firm, building systems designed to make complex information usable at scale. Through this position, she argues that the future will belong to institutions that not only collect data but can finally make sense of it.

Dealing With the Costs of Fragmented Data

Modern institutions often rely on dozens, if not hundreds, of separate software platforms and databases to store information. That setup frequently produces incompatible data-entry formats, duplicate records, and overlapping entries that never quite merge, leaving a tangled, inconsistent record of basic facts. As a result, key details are lost, and teams spend excessive time reconciling conflicting data rather than using it to guide action.

The consequences, in turn, are multiple: inconsistent reporting, wasted effort, and incorrect decisions based on incomplete information. Research has found that poor data quality can drain up to 25% of annual revenue from companies facing these problems. Institutions burdened by siloed data frequently report delays, misallocation of resources, and diminished trust in their own records.

For Nadira Pranatio, data fragmentation represents one of the most urgent infrastructure challenges facing modern organisations. That's why her work centres on designing frameworks that bridge isolated systems, translating and connecting data previously locked behind incompatible standards or departmental boundaries. Her current role as a software engineer consists of building pipelines that automatically unify disparate formats, ensure all records are complete, and harmonise records from different sources.

In doing so, her efforts aim to turn chaotic data stores into unified, usable knowledge bases that reflect an organisation's full reality.

Pranatio's View of Accessibility as a Key Asset

While consolidation addresses the fragmentation problem, Pranatio notes that integrated data alone can't guarantee better outcomes. Many systems remain too technical for even seasoned engineers to use on a day-to-day basis, with dense interfaces that can limit who's able to make use of the underlying data, narrowing the value of the system itself.

For her, usability is inseparable from infrastructure, and the interface becomes as critical as the architecture behind it.

That belief drives her work, where she seeks to ensure that anyone building on top of large data environments is working with applications they understand. She focuses on developer toolkits that explain how applications interact with complex datasets, reducing the need for teams to understand every internal mechanism. In practice, that means turning sophisticated back-end systems into approachable, dependable resources that organisations can adopt without friction.

Her view is that technology earns its relevance only when people can actually use it, and she argues that accessibility must guide every layer of the design process. She extends this principle beyond technical teams, drawing from her early work in civic technology, where public participation collapsed when tools became too complicated. As she says, 'Powerful technology doesn't mean much if only a few people can understand how to use it.'

Making Communication Smooth and Transparent

Another major challenge for Pranatio lies in interoperability: even when organisations have unified their internal data, those gains mean little if their systems can't communicate with others. Governments, hospitals, and multinational companies often rely on technologies built decades apart, each with different data schemas and security requirements. Pranatio explains, 'For data to serve its purpose, all parts of the system must be able to talk to each other. If they cannot, progress stops at the border.'

To counteract this potential problem, Pranatio ensures the frameworks she builds can properly allow institutions to exchange information. She designs adaptable data models that act as a shared digital language, making it possible for systems developed in completely different eras or regulatory environments to understand one another. This enables collaboration that would otherwise stall, from public-health agencies comparing regional trends in real time to supply-chain networks tracking goods across continents without losing visibility at jurisdictional boundaries.

She also emphasises transparency and auditability in the systems she builds. When sensitive data travels between different systems, it's important to have clarity on how it's processed, who has access to it, and what the end goal of it is. This is crucial to reduce the risk of misuse or misinterpretation and to support total oversight in sensitive contexts such as governance or public health.

Pranatio argues that ethical data design matters as much as technical design: systems should prioritize visibility of process, traceability of sources, and user accountability. In her view, infrastructure should not be a black box accessible only to technologists; rather, it must offer clarity to every stakeholder — from analysts to policymakers. Such clarity, she believes, empowers organisations to make decisions based on complete and trustworthy information, rather than fragmented or opaque data.

She adds, 'Transparency isn't just ethical, it's operational. You can't trust what you can't see.'

Building a New, More Connected Infrastructure

With years of experience building systems used across large and complex institutions, Pranatio believes data infrastructure will shape national and corporate strength in the decade ahead. In her view, the real measure of progress will not be the scale of an organisation's data, but who is actually able to benefit from it.

She believes the future depends on making advanced tools accessible to both developed and emerging economies, broadening the reach of systems that have historically served only a narrow set of users. As she notes, 'The future of data isn't about who has the most; it's about who can use it best.'

Taken together, Nadira Pranatio's perspective on how companies are dealing with their data reflects a broader argument about how modern data systems must evolve. The notions of accessibility, both technical and non-technical, and accountability have been the backbone of her work and seek to address the challenges institutions face today, suggesting a path in which data becomes a practical resource that strengthens operations, improves coordination, and supports institutions in acting with greater confidence.