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Common Streaming Data Application Use Cases

Common Streaming Data Application Use Cases

Consumers want experiences and information faster—quicker fraud notifications, speedily delivered products and services, and in-the-moment personalized offers. Sometimes, they want responses faster than your current tech stack allows.

This demand has made digital transformation a top priority for business executives, with 60% listing it as their most critical growth driver in 2022. And while many businesses use and process real-time data – they’re not seeing the real-time results needed to execute the sophisticated business use cases that modern consumers demand.

On the other hand, streaming data applications with Nstream reduce the complexity of typical streaming data architectures so companies can deliver the business experiences that consumers expect and crave.

We’ll cover how streaming data applications with Nstream enable use cases such as asset tracking and management, anomaly detection, and customer 360.

How streaming data applications make modern business use cases a reality

Traditional data streaming architectures are highly complex, involving multiple data systems that make it challenging (and costly) to run the processing, analytics, and advanced automation needed to execute modern business use cases. As a result, many companies are stuck relying on stale data or predictive models to inform business decisions being made that impact the current state of their business.

Nstream allows organizations to build a complete, stateful model of their enterprise to identify noteworthy changes, understand what they mean, and take action accordingly. How does this happen? Nstream’s technology innovations – including stateful services, streaming APIs, and real-time UIs – reduce the complexity of traditional streaming architectures so companies can:

Various enterprise customers have used the Nstream Platform to build streaming data applications that are running in production. Below are a few examples that showcase the scale at which these streaming data applications can operate:

Common streaming application use cases

Streaming data applications can help companies across industries execute sophisticated use cases that improve customer satisfaction, drive efficiencies, save on costs, and even create a competitive edge. Here are some examples of where real-time streaming data applications are already enhancing existing concepts:

Asset tracking and inventory management

Employed Americans spend at least two hours each day – or 25% of their workweek – searching for the documents, information, or people they need to do their jobs. This inefficiency isn’t limited to the average worker, either – entire companies often struggle with visibility into the whereabouts of assets as they journey throughout the supply chain. This poor asset tracking and management can lead to operational inefficiencies, asset loss or theft, and poor asset maintenance and management, among other challenges.

Streaming data applications allow businesses to access and see their entire landscape of assets and immediately act on changes as they arise. For example:

Anomaly detection

Often, the longer an anomaly goes undetected in your organization – whether that be a data breach or a missing shipment – the more damage it can cause. Since streaming data applications push data – rather than poll data – the state of a company’s business entities is updated at the speed of its fastest data source. That means that streaming data applications can help spot and begin to mitigate anomalies as soon as they appear – rather than minutes, days, or even months later.

Here are a few examples of how streaming data applications can support anomaly detection across verticals:

Customer 360 and real-time personalization

With 80% of customers stating they are more likely to buy from a company that offers personalized experiences, more organizations have begun working toward creating individualized customer journeys.

Streaming data applications are ideal for executing customer 360 use cases as they allow companies to analyze and act on large amounts of data without relying on

prohibitively complex or expensive data processing architectures. With streaming data applications, companies can maintain a full view of their business entities in real-time and implement business logic to respond to customers quickly during events or opportunities that matter most.

There’s no limit to potential use cases

Nstream is the fastest way to build full-stack streaming data applications – which also means it might be one of the fastest ways for you to accelerate your digital transformation efforts to see increased efficiencies, cost savings, and improved customer satisfaction. What’s more, streaming data applications are industry agnostic, allowing you to work from low-code templates or design an app that meets your specific company’s needs and challenges.

Want to see a streaming app in action? Check out how the city of Palo Alto gained greater visibility into real-time traffic trends with streaming data applications.