Traditional data pipelines extract, transform, and load data before it can be acted upon. But given the wide variety of sources and the scale and velocity by which the data is generated today, traditional data pipelines are not able to keep up for near real-time or real-time processing.
If your organization deals with big data and produces a steady flow of real-time data, a robust streaming data process will allow you to respond to situations faster. Ultimately, this can help you:
- Increase your customer satisfaction
- Make your company more competitive
- Reduce your infrastructure expenses
- Reduce fraud and other losses
Below are the specific features and benefits which ladder up these higher-level outcomes.
Competitiveness and customer satisfaction. Stream processing enables applications such as modern BI tools to automatically produce reports, alarms and other actions in response to the data, such as when KPIs hit thresholds. These tools can also analyze the data, often using machine learning algorithms, and provide interactive visualizations to deliver you real-time insights. These in-the-moment insights can help you respond faster than your competitors to market events and customer issues.
Reduce your infrastructure expenses. Traditional data processing typically involves storing massive volumes of data in data warehouses or data lakes. In event stream processing, data is typically stored in lower volumes and therefore you enjoy lower storage and hardware hardware costs. Plus, data streams allow you to better monitor and report on your IT systems, helping you troubleshoot servers, systems, and devices.
Reduce Fraud and Other Losses. Being able to monitor every aspect of your business in real-time keeps you aware of issues which can quickly result in significant losses, such as fraud, security breaches, inventory outages, and production issues. Real-time data streaming lets you respond quickly to, and even prevent, these issues before they escalate.