Every company today is in the process of becoming a data company. Data is leveraged by decision-makers not only to examine how their company has done in recent months, but also to gain specific insights into business operations and processes. These analytics influence business decisions and plans, and they play a critical role in increasing efficiencies, enhancing financial performance, and discovering new revenue streams.
Business data used to be processed in batches for analytics a few years ago. Now, real-time analytics is available, wherein, organizational data is analysed and queried as soon as it is created. In some instances, the action is taken a few seconds or minutes following the arrival of new data, rather than immediately.
However, businesses are increasingly using both approaches, particularly in industries where it is necessary to analyse data quickly in order to supply products or services, detect trends, and compete. After all, to provide a positive customer experience and retention, an ecommerce company would want immediate information regarding when and why its payment gateway went down. The diagnosis and resolution of such a problem might easily be delayed if historic data is evaluated in batches.
Here are some of the trends that will shape and drive real-time analytics adoption in 2022.
Increase in data volumes, velocity
At the organizational level, data quantities and velocity will continue their rising trend from recent years, surging more than ever before. This, paired with the convergence of data lakes and warehouses, as well as the need to make quick judgments, is projected to result in faster real-time analytics response times.
Systems will be able to consume huge amounts of incoming raw data without latency, whether it peaks for a few hours every day or for a few weeks every year, ensuring quick reactions to events and maximum business value. Furthermore, serverless real-time analytics solutions are likely to become more common, allowing businesses to create and run data-centric applications with indefinite on-demand scaling to manage a sudden influx of data from a specific source.
Increase in developer demand
Developers are likely to join analysts and technical decision-makers as the next big adopters of real-time analytics as the distinctions between real-time analytics and real-time analytical applications continue to blur due to the democratization of real-time data.
Every other company is now under pressure to use real-time data to automate operational decision-making, provide rapid, personalized customer service, or feed machine learning models with the most up-to-date data. Organizations that provide unrestricted access to real-time data to their developers in 2022, without needing them to be data engineering superheroes, will reap the benefits.
Business benefits across industries
Business benefits of real-time analytics will continue to drive adoption in 2022, regardless of industry. According to Future Enterprise Resiliency and Spending survey, the capacity to make real-time decisions will enable businesses to be more flexible, increase customer loyalty/outreach, and gain a competitive advantage. Furthermore, continuous data analytics, which notifies users as events occur, would aid in the improvement of supply chains and cost reduction, resulting in a quick return on streaming data pipeline expenditures.