What is Streaming Analytics?

Streaming analytics systems can consume, interpret, and act on real-time streaming data from a variety of sources, allowing you to act quickly as events are still unfolding. It can collect and analyse vast amounts of data in "streams" from always-on sources like sensor data, telematics data, system logs, social media feeds, shift data capture data from conventional and relationship databases, and location data, among others.

What Are Stream Analytics and How Does It Work?

Streaming analytics, also known as event stream processing, is the study of large amounts of current and “in-motion” data using event streams, which are continuous queries. These streams are caused by a particular event that occurs as a result of a specific action or series of actions, such as a financial transaction, equipment malfunction, a social message, a website click, or some other observable operation. The information can come from the Internet of Things (IoT), purchases, cloud applications, web interactions, mobile devices, and computer sensors, among other sources. Organizations can derive business value from data in motion using streaming analytics systems, just as they can with data at rest using conventional analytics tools. Real-time streaming analytics aid a variety of industries by identifying opportunities and risks in real time.

Streaming Analytics Has a Lot of Benefits:

  • Visualization of data: Organizations can monitor their main performance indicators (KPIs) on a regular basis by keeping an eye on the most relevant company data. Streaming data can be tracked in real time, enabling businesses to know exactly what is going on at any given time.
  • Business knowledge: If an unusual business occurrence happens, it will first appear in the appropriate dashboard. It can be applied to cybersecurity to automate threat detection and answer. Abnormal activity in this field should be immediately reported and investigated.
  • Increased ability to compete: Streaming data can help businesses identify patterns and set benchmarks more quickly, giving them a competitive edge. They will be able to outrun their rivals who are still relying on the slow method of batch analysis.
  • Avoiding damages: Security breaches, production problems, consumer turnover, stock market meltdowns, and social media crises can all be avoided or at least reduced with the help of streaming analytics.
  • Analyzing typical company processes: Streaming analytics gives businesses the ability to ingest and analyse real-time data in real time.

What Are Some Use Cases for Streaming Analytics in the Real World?

Cybersecurity, financial services, banking, manufacturing, the oil sector, healthcare, and many other sectors have used real-time analytics on streaming data. Listed below are a few examples:

  • Manufacturing: A manufacturer can spot problems and fix them before a product leaves the production line by analysing the data from these sensors in real time. This increases production and operational productivity while also saving money. Read our reference article for more information on Industrial IoT and IoT data management.
  • Cybersecurity:  As a result, rather than responding after a problem arises, the attack is halted before it can cause any damage.
  • Hospitality industry: Streaming analytics could be used to monitor reservations in real time. When a chain notices a spot with high availability in the late afternoon, it will text or email promotional offers to frequent visitors in the area to fill the empty rooms that night. 

Final Words:

It is very necessary for the companies to make use of the real-time initiated data immediately before losing the value of data. Data that loses its value ultimately results in incurring additional costs like operational, administrative, reputation damage, potential legal action, reduction in productivity and many more. Streaming analytics provides deeper insights with the help of data visualization, offers information about customer behaviour, and to be competent in nature. The strategic business shift towards real-time, which accurately provides forecasts for faster decision making, is also expected to drive the market growth. 

Streaming Analytics Market: 25.7% CAGR

Projected Revenue: 60.98 billion from 2021 to 2027

For deeper dive check the full report here:

Published Date : March-2021

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