How Real-Time Business Logic Leads to Real-Time Business Decisions
On its surface, business logic might look like a long list of tactical rules, procedures, guidelines, and best practices that guide thousands of small decisions a company makes daily. However, thinking of business logic like a Monet painting is helpful – all the small details add up. What might look like hundreds of tiny decisions up close, reveals a larger picture of how a company operates and makes critical business and customer decisions.
However, many companies today still struggle to implement business logic in real-time streaming context, instead relying on traditional data processing approaches that delay actionable insights. This reliance will prove to be a growing problem in a business landscape that increasingly requires fast-paced decision-making to remain competitive and innovate.
In fact, modern organizations will need to find ways to implement business logic in real-time context – such as with streaming applications – to survive and thrive moving forward.
The importance of full-context business logic
Business logic can be best understood by the phrase: “The whole is greater than the sum of its parts.” Tactically, business logic is the process by which applications interpret the meaning of data according to a model of how your business functions and the goals you are trying to achieve. Companies might rely on business logic to manage and access large quantities of data, and developers might use business logic to automate actions, such as sending notifications based on specific data segments. Taken as a whole, however, business logic can be understood as how all these tactical actions work together to make a business run holistically and strategically.
Today, it’s not enough to implement business logic – organizations that want to excel and innovate in today’s fast-paced environment need to implement business logic in real-time streaming context to satisfy growing customer expectations and demands.
This means executing rules, processes, and decisions in real-time (not minutes, hours, or days later) and with the full context of what’s happening within all relevant parts of the business.
Consider the use case of fraud. For a bank dealing with a potential fraud case, whether to flag and freeze a credit card depends on the context. If there are indicators of a trip, such as recent ticket purchases and other local expenses, a freeze or flag could be unnecessary and frustrating for the customer. However, if there are no trip or travel history indicators, a freeze or flag may be justified and save the bank and customer time and money.
Customer 360 initiatives are also a great example of the difference between implementing business logic – and implementing in-stream, contextual business logic. For example, this might look like the difference between an Instacart shopper arriving at the grocery store only to find the apples are out of stock, and the Instacart shopper receiving a notification to reroute to a different, fully stocked store before he arrives and begins shopping.
In other words, real-time, full-context business logic empowers organizations to execute modern and more sophisticated business applications that consumers increasingly expect and require. Organizations that fail to execute real-time business logic with the proper context risk repercussions such as poor customer satisfaction, hits to brand reputation, and ultimately lost revenue.
The challenge of real-time business logic
Organizations using a store-then-process architecture will also find that increasing the data rate to decrease latency will drive up the cost of storage required to buffer data until it is processed. In the end, many companies must prioritize latency, context, or cost.
Companies need a way to recapture this lost value to gain full context across all data streams. Achieving these steps would enable business logic to act on complete data in the truest sense of real-time.
How streaming applications provide real-time business logic
The ultimate goal of real-time streaming applications is to run business logic directly on streaming data. In other words, real-time streaming applications are a tool to successfully implement business logic in real-time streaming context, or as the state of your business changes.
This is because real-time streaming applications continuously push differential entity model updates in sync with data streams. Organizations can maintain their store-then-process approach to feed data lakes and long-term storage, but can also utilize a process-and-maybe-store approach for real-time streaming applications in parallel.
With streaming applications, businesses can take advantage of streaming data to enable real-time observability, analysis, and automation – or to use business logic to enhance and fine-tune their services. The benefits of streaming applications to implement real-time business logic can be applied across industries. Here are a few examples:
The Dubai Roads and Transport Authority (RTA) uses in-stream business logic to make the movement of freight vehicles across the UAE more efficient. By having better control over the data they collect, RTA can dynamically display all RTA vehicles, in real-time, on a geospatial map.
As a result, vehicle inspectors, operational monitoring teams, and regulators can better understand vehicle movements, driver behavior, road conditions, and traffic incidents.
A major telecommunications service provider uses real-time business logic to provide in-the-moment information to field service crews, IT departments, and customer service representatives so that they can react to customer needs instantaneously.
Build applications with better business logic
To remain competitive in today’s market, organizations must create applications with real-time business logic, enabling observability, analysis, and automation on top of real-time streaming data.
Nstream is the first general-purpose platform for running business logic — the lifeblood of streaming applications — directly on data in motion. Nstream is built by developers, for developers. Our tool not only enables you to quickly build streaming data applications but also allows you to see how your data relates to the needs of the business — in real-time.
Once you get started with a real-time streaming application, the use cases are endless. To get the ideas flowing, check out our video on how to get real-time observability into everything you care about.