Get into the Minds of Your Customers with Real Time Data Stream Processing

Posted by superfast processing on July 10th, 2019

The extreme level of competition between modern-day businesses has created a need for observing and analyzing industry trends. AI-based technologies have provided a way to effectively turn data into insights and hence, such technologies are frequently used by many companies. However, in many use cases, Fast data processing methodology serves as a major bottleneck.

The New Age of Processing

In traditional processing scenarios, data is first stored in a database and only then applications can query or compute the data as per requirement. While this approach has worked well for a long time, it is not ideal for many business use cases. Case in point being: Emerging technologies like IoT generate massive amount of data via sensors continuously. Storing this data and then running analytics can delay the process of ‘useful’ insight generation. For example, if the data sent by a camera sensor that shows robbers entering a house is not processed at the right time, it will delay the triggering of the alarms connected to the camera via IoT network. But with real time processing, it is possible to process the breach and trigger the alarm at the very instance robbers enter the house. The process of stream processing has many stages i.e. logic for applications, analytical capabilities along with data queries, all of which exist simultaneously. Data streams flows through these different stages and get processed as soon as they are received by the system.

Just like the case above, there are many use cases in day-to-day business scenarios that can be improved with real time data stream processing.

The Challenge of Real Time Data Stream Processing

As mentioned before, businesses of today rely heavily on data analytics. Real time data stream processing makes analytics more powerful as insights are derived in real time. These insights can be used immediately for actual business gains; which is why, real time data stream processing is so useful. However, processing large amount of data in real time requires state-of-the-art hardware for efficient computing performance. Spending too heavily on expensive hardware resources may offset the benefit you are likely to get from your new insights. A better option is to outsource your processing tasks to a capable vendor that already has the computing infrastructure in place.

What to Look for in Your Real Time Data Stream Processing Outsourcing Vendor?

For efficient real time data stream processing, you need the fastest processing solutions. New tech solutions that come with in memory and parallel processing capabilities are needed to transform copious amount of business data into useful insights. Moreover, you would need data base analysts that can help you accomplish large amount of work in the least amount of time.

Summary

Real time data stream processing provides a great way to process and analyze data in real time. If you have a business and want to unearth vital insights from your customer base, real time data stream processing is a technology that can take you inside the minds of your customers by analyzing their every move.

Superfastprocessing excels at providing completely secure cloud-based millisecond processing solutions. Backed by a team of 100 qualified DBAs and program managers, it has already delivered many successful projects for finance and telecom companies.