Today, every business is on its way to becoming a data company. Data is used by decision-makers not only to see how their organization performed in the previous few months but also to generate detailed insights (the what and why) into business processes and operations. These analytics, powered by tools like Tableau, help to inform business decisions and strategies, as well as play a critical role in driving efficiencies, improving financial performance, and identifying new revenue sources.
Business data used to be processed in batches for analytics a few years ago. Real-time analytics is now available, in which organizational data is processed and queried as soon as it is created. In some cases, the action is not taken immediately, but rather a few seconds or minutes after new data is received. However, both practices are increasingly being adopted by businesses, particularly in sectors where it is necessary to analyze data immediately in order to deliver products or services, understand trends, and compete. After all, an eCommerce company would require immediate information about when and why its payment gateway went down in order to ensure a positive customer experience and retention. The detection and resolution of such an issue could easily be delayed in the case of historic data analyzed in batches.
Here are some trends that will shape and drive real-time analytics adoption in 2022.
Surge in data volumes, velocity
Continuing the recent trend, data volumes and velocity at the organizational level will continue to rise, surging more than ever before. This, combined with the convergence of data lakes and warehouses, as well as the need to make quick decisions, is expected to drive improvements in real-time analytics response time.
Systems will be able to ingest massive amounts of incoming raw data without latency, whether it peaks for a few hours every day or for a few weeks every year, and faster analytical queries will be possible, ensuring instant reactions to events and maximum business value. Furthermore, serverless real-time analytics platforms are expected to enter the mainstream, allowing organizations to build and operate data-centric applications with infinite on-demand scaling to handle a sudden influx of data from a specific source.
“Overall, 2022 will be a challenging year for keeping up with growing data volumes and performance expectations in data analytics,” said Chris Gladwin, CEO and cofounder of Ocient. “More organizations will seek continuous analytics and higher resolution query results on hyperscale data sets (trillions of records) to gain deeper, more comprehensive insights from an ever-increasing volume and diversity of data sources.”
Rise in developer demand
As the lines between real-time analytics (which provides instant insights to humans for decision-making) and real-time analytical applications (which take decisions automatically as events occur) continue to blur as a result of the democratization of real-time data, developers are expected to join technical decision-makers and analysts as the next big adopters of real-time analytics.
According to a report from Rockset, which provides a real-time analytics database, developers will use real-time data analytics to build data-driven apps capable of personalizing content/customer services, A/B testing quickly, detecting fraud, and serving other intelligent applications such as automating operational processes.
“Every other business is now feeling pressure to use real-time data to provide instant, personalized customer service, automate operational decision-making, or feed ML models with the most up-to-date data.” Businesses that give their developers unrestricted access to real-time data in 2022, without requiring them to be data engineering heroes, will leap ahead of laggards and reap the benefits, according to Dhruba Borthakur, cofounder and CTO of Rockset.
Off-the-shelf real-time analytics capabilities
Real-time analytics based on off-the-shelf capabilities are expected to become more mainstream, easier to deploy, and customize in 2022 and beyond, according to Donald Farmer, principal of Treehive Strategy. This will be a departure from the current practice of writing code in-house or sourcing it from highly specialized vendors, and it will drive the adoption of real-time analytics in retail, healthcare, and government.
According to Farmer, real-time analytics based on off-the-shelf capabilities have mostly been used in sectors such as transportation (for customer support) and manufacturing (for production monitoring). Farmer’s professional experience includes working on several of the market’s leading data and analytics technologies. Previously, he led design and innovation teams at Microsoft and Qlik.
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Business benefits across sectors
The business benefits of real-time analytics will continue to drive adoption in 2022, regardless of industry. According to IDC’s Future Enterprise Resiliency and Spending survey, the ability to make real-time decisions will make enterprises more agile, increase customer loyalty/outreach, and provide a significant competitive advantage. Furthermore, continuous data analytics, which alerts users as events occur, would aid in improving supply chains and lowering costs, resulting in a quick ROI on streaming data pipeline investments.
According to Rockset, one oil and gas company was able to increase its profit margins by 12% to 15% after implementing real-time analytics.
According to Meike Escherich, associate research director for the European Future of Work at IDC, there has already been a significant uptake in the implementation of real-time analytics, with one in every three European companies using them for measuring team performance or planning to do so within the next 18 months. Similarly, Gartner predicts that by 2022, more than half of major new business systems will include continuous data intelligence.
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