Real-time data stream processing

Leverage Data Value for Your Business with Real-Time Data Stream Processing

Data value is dependent on many factors such as data relevance, data volume and the amount of time spent in deriving value from data. However, due to a rise in competition and a shorter window of opportunities, businesses are looking for data that can be put to good use in real-time. Nowadays, the window of opportunities to exploit insights has become very short. This has happened because competitors are often using similar databases and coming to the same conclusion after analyzing it. Hence, to really make the most out of a database, it is imperative that you utilize it before anyone else does, which can be done with real-time data stream processing. Also, there are many fields, in which, real-time data stream processing is extremely useful e.g. IoT. Therefore, real-time data stream processing has become more of a necessity rather than a luxury.

3 Compelling Reasons Why Real-Time Data Stream Processing Is Essential

  1. Nature of data – In some business use cases, like in IoT, data is only available as a stream of events. To perform batch processing on this type of data, you need to store the data first and then form batches, on which, processing can be done. This process is inefficient for use cases like IoT where the result of processing needs to be known in real-time. Real-time data stream processing is tailor-made for such business use cases as it provides the results in real-time.
  2. Hard to store data – In some cases, data generated is so large that it becomes tough to store it in a standard storage device like HDD. In such cases, real-time processing is more efficient and cheaper.
  3. Low processing power requirements – When you accrue data over a period of time, you form a large database that requires high processing power for appropriate execution. On the other hand, real-time data stream processing executes a small quantity of data in real-time, which requires less processing power.

Why You Need Fast Data Processing on the Cloud?

Fast data processing like real-time data stream processing can be done in-house or outsourced to a vendor that offers cloud-based processing services. Considering the nature of businesses these days, cloud-based processing solutions work a lot better than on-premise solutions. Below are some reasons for that:

  1. Cost efficiency and fewer hassles – Buying high-powered computer hardware and upgrading it regularly to meet emerging requirements can be a costly affair. On the other hand, when you outsource the processing work to a competent vendor, you get processing capabilities without any major investments. Also, there is no need to manage or upgrade the hardware.
  2. Multiple points of redundancy – A cloud-based processing services provider like Superfastcomputing offers multiple points of redundancy for the data by replicating the same data across multiple data centers. This helps in preventing data destruction due to natural or human-caused catastrophes.
  3. Access to DBAs and technicians – Processing large amount of data requires you to have DBAs and technicians that can guide the project to successful completion. An outsourcing company has access to all these resources, which makes them a great option for fast processing work.
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