Since companies in every industry may have data streaming from multiple sources, analyzing such data in real-time can be helpful for providing valuable insights. Streaming analytics tools provide advancements in the streaming of business intelligence (BI) by improving access to data that is changing constantly, including social media activity, sales leads, websites, mobile apps, customer activity, etc.
While traditional analytics tools extract information from data at rest, streaming analytics is useful for finding the value of data in motion, i.e., in real-time. Using the power of data to constantly monitor company informational and data assets, companies can reduce operating costs, improve customer experience and increase efficiency by leveraging streaming analytics platforms.
Reduce Operating Costs
Streaming analytics may be attractive for many businesses due to its capability for automation, which may help to reduce certain operating costs, such as the following:
- Basic utility costs – Streaming analytics can provide real-time data on utility costs such as electricity usage, temperature anomalies and water usage. Hotels, for example, may benefit greatly from such data, which can provide instant insight into rooms or areas that could be adjusted for decreased energy costs – such changes can be automated through a streaming analytics tool.
- Supply chain and production – Companies that depend upon their supply chain and production line can use streaming analytics to quickly identify problems or issues before a finished product departs the production line, which can improve operational efficiency and reduce overall costs.
- Fraudulent activity – Streaming analytics can be of great value to cybersecurity efforts by helping to identify suspicious behavior. By flagging potentially fraudulent activity based on pre-determined criteria, potential cyberattacks may be stopped before they occur, which can ultimately reduce or prevent losses associated with fraudulent activity. The same concept is applicable for financial transactions.
Improve Customer Experience
Streaming analytics seeks to blend automation, analytics and machine learning to help companies make important decisions as events occur in real-time to migrate from reactive decision-making to proactive management of business. This can be highly effective in the area of sales and the customer experience. Industries such as hospitality, financial services, retail, etc., can make use of streaming analytics tools such as real-time personalization to provide a one-of-a-kind customer experience in order to potentially improve sales. Real-time personalization tools using machine learning to capture a customer’s online search behavior in order to suggest new products or issue alerts when the customer experience is flagged for unfavorable issues is another example. Streaming certain data may also help companies identify trends among competitors, which can help them quickly establish better benchmarks and make adjustments to the overall customer experience.
Every day, data is produced at a high volume – at the start of 2020, it was estimated that the digital universe would consist of approximately 44 zettabytes of data,1 and the world’s overall volume of data is expected to continually increase at an unprecedented rate. Therefore, decision velocity has become increasingly important for a company’s overall operating efficiency – essentially, important decisions may be made faster when there is access to more timely data. Additionally, streaming analytics can be integrated with other business applications, including information technology (IT), finance, marketing and sales, by means of customizable data dashboards. Streaming analytics has the ability to be highly scalable, making it able to adapt and handle a high volume of data streaming without compromising its performance.
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- How Much Data is Created Every Day? www.seedscientific.com. Jan. 30, 2020.