Why Real-Time Intelligence Is a Game Changer

“Real-time intelligence is where the true value of data comes to life,” says Thakshila, a data specialist at Novon. “It’s not just about collecting information — it’s about being able to act on it as it’s being generated. Whether that’s spotting fraud, adjusting inventory to match sudden demand, or triggering predictive maintenance, this is data at its most powerful.”

According to Thakshila, real-time intelligence allows businesses to handle vast volumes of time-sensitive data and make decisions when they matter most. “It centralises data in motion. That means we can query, transform and gain insights from structured and unstructured sources while they’re moving through the system — not hours or days later.”

Three Platforms, Three Approaches

“Each of the big platforms — Azure, Databricks and Microsoft Fabric — approach real-time intelligence differently, and that’s what makes this space so interesting to me,” she says.

Databricks: Performance and Scale

“Databricks is my go-to when performance and scale matter most. Its Structured Streaming engine is incredibly powerful, especially for machine learning and advanced ETL workloads. If you’re doing high-volume, low-latency processing and your team is comfortable with complex engineering, Databricks is the way to go.”

Azure: Modular and Event-Driven

“For log processing, event ingestion or IoT data, Azure’s native services like Event Hubs, Stream Analytics and Data Explorer are spot on. They’re modular, integrate easily with existing Azure environments, and you can get dashboards up and running with minimal effort.”

Microsoft Fabric: Real-Time for Business Users

“Fabric is the most exciting for business users. It’s not designed for ultra-high-frequency decisioning, but for real-time visibility and operational dashboards, it’s a game changer. I’ve watched teams spin up live dashboards in minutes, trigger alerts and use Copilot to surface insights — all without touching code.”

Choosing the Right Tool Starts with the Right Questions

“One of the biggest mistakes I see is businesses jumping straight into a tool because it’s popular or powerful,” Thakshila says. “What they should be doing is asking: what are we trying to solve? What’s the latency requirement? What kind of data are we working with?”

“The technology should serve the business, not the other way around.”

When to Use Databricks

“Databricks isn’t the simplest tool for business users, but for engineering-heavy environments with serious performance requirements, it’s unmatched. The Structured Streaming engine gives you full control and excellent scalability.” It’s the right fit when advanced data transformations or machine learning are part of the picture.

When to Use Azure

“Azure is brilliant for modular, event-driven solutions. It works really well when you need to process IoT data, system logs or user activity in real time.” Thakshila notes that the integration with Power BI is a real win: “I’ve deployed Stream Analytics jobs that connect to Event Hubs and light up a Power BI report in minutes.”

When to Use Microsoft Fabric

“Fabric is for analysts or operations teams. If your team needs real-time insight but doesn’t have data engineering capacity, this is the most accessible tool on the market.” The tight integration with Power BI and OneLake — plus Copilot — puts real-time analytics directly into the hands of business users. “It’s not for microsecond latency, but it gets the job done for operational dashboards and alerts.”

Real Advice: Fit-for-Purpose, Lean and Cost-Aware

“Start with purpose, not hypotheticals,” Thakshila advises. “I see far too many systems built for imaginary use cases. Design for what your business actually needs.”

One of her first recommendations is to look for cost sinks. “Eliminate duplication. I’ve helped companies save tens of thousands simply by reducing how often certain queries are run. High-frequency dashboards are expensive when they don’t offer high-value insight.”

She also champions lean data management. “Massive data warehouses aren’t always necessary. Reduce complexity by breaking things down to the datasets you really need.” And don’t forget licensing. “Licences are often an invisible cost. I always recommend a review — especially when tools charge per user. It’s a quick win.”

The Bottom Line

“Real-time intelligence isn’t just a trend — it’s a necessity. It’s about staying competitive, agile and proactive.”

“The goal isn’t just to be fast — it’s to be fast where it matters. That’s what we help our clients do at Novon: build fit-for-purpose data strategies that make real-time intelligence work in the real world.”