The old slogan, โmoving at the speed of business,โ feels very relatable in the modern world. Immediacy is in high demand, and processes must rise to the occasion. This is particularly true when it comes to data. Weโre more connected, digitized, and inundated with data points.
With this abundance of data comes a wealth of opportunity, particularly for the businesses that collect and analyze it. Parsing data well means gaining actionable insights and making informed business decisions. If youโre moving at the speed of business, that means real-time data processing.
What is Real-time Data Processing?
Real-time data processing refers to the instantaneous ingestion and analysis of incoming data points. A continuous data stream is processed as received, and outcomes are stored for review or record.
This continuous flow is also called stream processing. Real-time processing differs from batch processing, which ingests and retains data to be reviewed at a later time or date.
What Are the Benefits of Real-time Data Processing?
Real-time stream processing enables businesses to interpret data on demand and make decisions accordingly. The benefits of real-time decision-making are twofold: first, companies can review data and introduce new business decisions based on relevant and current information, increasing agility and decreasing risk. Secondly, real-time processing can be used to identify anomalies in the system, alerting to fraud or non-compliance issues so administrators can take action swiftly.
This approach also lowers operational costs, eliminating the need to store large swaths of data as required in batch processing alternatives. Since data is processed continuously in a real-time analytics database, less manual intervention is required. Insights can be retrieved, read, and responded to by any team member with access to the processing platform.
How Does Real-time Data Processing Work?
The finer details will depend on your unique environment, but the foundation is the same:
To start, when data is generated, the server receives the input. This data can be rendered from single or multiple sources. Once the data is ingested, the system determines how to process the real-time data. Depending on the answer, it will issue an order of what to do based on the information it has received. Depending on the use case and type, the data may need to be sorted and stored, analyzed and reported, or checked to generate alerts or initiate critical actions.
Why is Real-time Data Processing Important?
Processing data in real-time is important for organizations that want to offer the best experience to their end users and make well-informed business decisions. Having the most current data analysis at your fingertips means the ability to act swiftly based on insights, saving resources otherwise lost to trial-and-error or manual processing.
