In a recent report from Information Services Group (ISG), a global technology research firm, findings suggest that by 2027, more than three-quarters of enterprises are expected to adopt real-time data processing to enhance responsiveness to customer needs. This shift is largely driven by the increasing demand for AI-powered interactive applications that require timely data analysis.
Real-time processing allows companies to react promptly to events, an approach that could redefine operational efficiency across various sectors. Historically, real-time data processing was limited to high-performance industries such as financial services, where immediate responsiveness is critical. Currently, however, only 22 per cent of enterprises employ real-time data analysis, indicating a significant gap and room for growth.
The report highlights that organisations are moving away from traditional batch processing methods, which rely on periodic data updates, toward models that support continuous data streaming. As Mat Aslett, director of research at ISG Software Research, noted, “Real-time data processing lets enterprises operate at the speed of business, acting on events as they happen.” This kind of agility is crucial for maintaining competitiveness in an ever-evolving market.
ISG’s analysis also places emphasis on the technological advancements that have made real-time processing more accessible. The research evaluated over 25 software providers, concluding that many of the leading firms have developed solutions capable of fulfilling nearly 80% of the requisite functionalities needed for effective data management. With businesses increasingly recognising the importance of rapid data analysis for customer engagement and decision-making, this evolution could potentially transform how data-driven applications are built and deployed.
In a related trend, the demand for hybrid data platforms is expected to surge as enterprises embrace Generative AI technologies. By 2027, more sophisticated applications leveraging AI for personalised experiences are projected to drive investments in hybrid systems that seamlessly integrate operational and analytical capabilities. This development aligns with findings from another ISG report, which anticipates significant growth in intelligent applications requiring robust data processing tools.
Moreover, as companies consider their future data architecture, the need for a cohesive strategy encompassing both real-time and traditional batch processing approaches becomes evident. Effective governance of both types of data is paramount for optimising operational efficiency and ensuring comprehensive insights are accessible across the organisation.
While the enthusiasm for real-time data processing is palpable, challenges remain. The technical barriers inherent in integrating advanced data infrastructures can be daunting, particularly for smaller enterprises with limited resources. However, the continued maturation of software solutions is gradually reducing these complexities, making it feasible for a broader range of organisations to enter the real-time domain.
Mark Smith, a partner at ISG, succinctly summarised this sentiment, stating, “To remain competitive, enterprises constantly need to analyse more data and act on it in real time, which requires the right real-time architecture and enterprise software.” The ISG Buyers Guides for Real-Time Data thus offer essential insights, assisting businesses in navigating their software options to harness the full potential of real-time data analytics.
The findings from ISG’s research not only underscore the urgency for enterprises to adapt to these emerging technologies but also reveal a broader trend towards automation and efficiency that is being seen across various sectors. As organisations implement these tools, the landscape of data management and customer interaction stands poised for a transformative shift.
Reference Map
- ISG report on enterprises adopting real-time data processing by 2027
- Insights on emerging hybrid data platforms from ISG
- Studies highlighting the role of advanced data platforms in AI application development
Source: Noah Wire Services
Subscribe to Industry Updates
