Today, every company is in the process of becoming a data company. Decision-makers leverage data not just to see how their organization performed in the past few months, but also to generate detailed insights (the what and why) into business processes, operations. These analytics, driven by tools such as Tableau, inform business decisions and strategies and play a crucial role in driving efficiencies, improving financial performance, and identifying new revenue sources.
A few years ago, business data used to be processed in batches for analytics. Now, real-time analytics has come on the block, where organizational data is processed and queried as soon as it is created. In some cases, the action is not taken instantly, but a few seconds or minutes after the arrival of new data. However, both the practices are increasingly being adopted by enterprises, especially in sectors where the need is to analyze data immediately to deliver products or services, understand trends, and take on rivals. After all, an ecommerce company would need instant information about when and why its payment gateway went down to ensure customer experience and retention. In the case of historic data analyzed in batches, the detection and resolution of such an issue could easily get delayed.
Here are some trends that will shape and drive the adoption of real-time analytics further in 2022.
Surge in data volumes, velocity
Continuing the trend from recent years, data volumes and velocity at the organization level will follow the upward trajectory, surging more than ever before. This, combined with the convergence of data lakes and warehouses and the need to take quick decisions, is expected to drive improvements in the response time on real-time analytics.
Systems will be able to ingest massive amounts of incoming raw data – no matter whether it peaks for a few hours every day or for a few weeks every year – without latency and faster analytical queries are likely to become possible, ensuring instant reactions to events and maximum business value. On top of that, serverless real-time analytics platforms are also expected to go mainstream, which will allow organizations to build and operate data-centric applications with infinite on-demand scaling to handle the sudden influx of data from a particular source.
“Overall, 2022 will be a challenging year for keeping up with growing data volumes and performance expectations in data analytics,” Chris Gladwin, the CEO, and cofounder of Ocient, told Venturebeat. “We will see more organizations looking for continuous analytics and higher resolution query results on hyperscale data sets (trillions of records) to gain deeper, more comprehensive insights from an ever-growing volume and diversity of data sources.”
Rise in developer demand
As the lines between real-time analytics (which provides instant insights to humans to make decisions) and real-time analytical applications (which automatically take decisions as events happen) continue to blur on the back of the democratization of real-time data, developers are expected to join technical decision-makers and analysts as the next big adopter of real-time analytics.
According to a report from Rockset, which offers a real-time analytics database, real-time data analytics will see a sharp rise in demand from devs who will use the technology to build data-driven apps capable of personalizing content/customer services as well as to A/B test quickly, detect fraud, and serve other intelligent applications like automating operational processes.
“Every other business is now feeling the pressure to take advantage of real-time data to provide instant, personalized customer service, automate operational decision-making, or feed ML models with the freshest data. Businesses that provide their developers [with] unfettered access to real-time data in 2022, without requiring them to be data engineering heroes, will leap ahead of laggards and reap the benefits,” Dhruba Borthakur, cofounder and CTO of Rockset, said.
Off-the-shelf real-time analytics capabilities
In 2022 and beyond, real-time analytics based on off-the-shelf capabilities are expected to become more mainstream, easier to deploy, and customize, Donald Farmer, the principal of Treehive Strategy, told Venturebeat. This will be a departure from the current practice where the code is written in-house or sourced from highly specialized vendors and drive the adoption of real-time analytics in retail, healthcare, and the public sector.
So far, real-time analytics based on off-the-shelf capabilities has mostly been used in sectors such as transport (for customer support) and manufacturing (for monitoring production), Farmer noted. Professionally, Farmer has worked on several of the top data and analytics technologies in the market. Additionally, he previously led design and innovation teams at Microsoft and Qlik.
Business benefits across sectors
Business benefits of real-time analytics, regardless of the sector, will also continue to drive adoption in 2022. As per IDC’s Future Enterprise Resiliency and Spending survey, the ability to make real-time decisions will make enterprises more nimble, boost their customer loyalty/outreach, and offer a significant advantage over the competition. Plus, continuous data analytics, which alerts users as events happen, would help towards improving supply chains and reducing costs, bringing about fast ROI on streaming data pipeline investments.
As per Rockset, one oil and gas company was able to increase its profit margins by 12% to 15% after adopting real-time analytics.
Meike Escherich, associate research director for European Future of Work at IDC, notes they have already recorded a significant uptake in the implementation of real-time analytics, with one in three European companies either already using them for measuring team performances or planning to do so in the next 18 months. Similarly, Gartner too predicts that more than half of major new business systems will incorporate continuous data intelligence in 2022.
留下你的回應
以訪客張貼回應