Data virtualization as a solution — Part 3: time pressure and capacity bottlenecks

Organizations must react quickly to regulation, market shifts and crises while systems grow ever more complex. This third part looks at the time pressure and capacity bottlenecks that new requirements create, and how data virtualization relieves them.

Companies are pushing an ever-increasing wave of requirements ahead of them.

Rising requirements, growing complexity

Rate changes, mergers, divestitures, sanctions and new accounting standards generate a constant stream of demands on IT. IT has to prioritize, so requests are delayed or dropped, and users fall back on manual work — spending most of their time collecting and preparing data rather than interpreting it. Ad-hoc questions and scenario analysis become impractical, so problems are spotted late.

No separation of duties — and brittle business logic

Storing and administering data well demands technical rigor that rightly belongs to IT; interpretation and business logic belong to the specialist departments. Traditional warehouses can't separate the two, so every change becomes a joint project with constant coordination. Specialized logic ends up either baked into IT-managed pipelines (only IT can change it) or scattered across spreadsheets, scripts and dashboards (impossible to track, and inconsistent across versions).

This separation of duties reduces the pressure on the company's IT and at the same time increases the speed of implementation.

Optimal work distribution with data virtualization

Data virtualization decouples storage from consumption: IT keeps the databases consistent and reliable, while authorized users transform and combine data within their permissions, apply business logic, and feed results straight into their applications. Logic lives centrally in version-controlled repositories — auditable, with full change history, reusable and composable into new virtual models. The result eases IT's load, speeds delivery, and resolves capacity constraints durably.