Real-time data: A game changer for the enterprises of tomorrow
Article by Deb Dutta, General Manager, Asia Pacific & Japan
Customers today are obsessed with real-time experiences that are a part of their daily lives. Because their digital world overlaps with their physical reality, they want to access products, services, and information wherever they are, through any connection they have, on any device, and personalized.
From ordering a coffee on a mobile app to receiving personalized recommendations on a website or streaming TV app, truly data-driven businesses are building these applications to engage customers and build new revenue models.
The data behind these apps need to be available in real-time to power them. IDC predicts that by 2025, nearly 30% of data generated will be real-time. Meanwhile, 40% of spending on data capture and movement technology in the Asia Pacific Excluding Japan (APEJ) will be on streaming data pipelines that enable a new generation of real-time simulation, optimization, and recommendation capabilities.
Enterprises looking to stay ahead of the competition in the data-driven world must have data infrastructure that meets this demand for real-time digital user experience. Succeeding in today’s competitive business environments, ultimately comes down to insightful and timely data-driven decision-making. Efficiency in data usage has never been more critical to business success, and the ability to process and analyze data in real-time will be crucial in reducing costs and speeding up time to market. You are either in real-time or out of time.
However, extracting true value from rich data repositories continues to be a complex challenge for developers and enterprises – especially for real-time use. Today, most data functions used by businesses for their applications are monolithic and inefficient, rather than designed to meet customer expectations quickly. This increases data latency which may be acceptable in use cases such as generating analytics and reports. However, it can be a significant setback for today’s real-time use cases such as fraud detection, in-the-moment product recommendation engines, click stream analysis, mobile coffee orders, and device to-data analysis (IoT) for example.
Why enterprises must tap on the data-intrinsic value of ‘now’
To optimize decision-making, enterprises have focused efforts on improving data literacy within their teams to enable the gathering, storing and analyzing of large datasets. Although they have been able to drive considerable automation and growth with this data, it is only the tip of the iceberg and many businesses are still some ways off from unlocking limitless innovative transformations that data can enable.
In the quest for secure, smarter workflows within digitalized environments, enterprises have explored several tools such as data lakes that could enable them to fully leverage the existing information at hand. These tools have their place in providing high-level, backward-looking data analytics (the deep lane of data) by aggregating internal and external sources, but were unable to manage the rapid ingestion of operational data and deliver quick strategic responses to business events (the fast lane of data). The emergence of cloud-based data architectures and new data storage models are enabling organizations to dramatically reduce the cost of harnessing data in motion and data at rest for use in real-time.
These new technologies help mobilize precious customer information previously trapped in silos to fuel real-time, engaging applications with speed. While there are tools to aid in the elimination of external data silos, complex data architectures used to harvest that data can inadvertently create new operational data silos or swamps. Entering into a rapidly advancing technology landscape, enterprises that do not bridge these gaps will fall back and fail to tap on the transformative benefits of real-time data.
So, how can enterprises truly make data work for them, drive critical processes, and customer satisfaction, and increase revenue?
Delivering more value, faster with real-time data
Siloed data from various enterprise applications, stored on-premises or even on public clouds, usually has the propensity to be unused and redundant. The key to transporting data, as a high-value yet under-leveraged asset, towards building capabilities to manage its scale and growth, lies in freeing data so that it is available to the entire data ecosystem including data lakes, data warehouses, etc.
Organizations need to bridge data flow from high-value business events to real-time applications at the moment. When business leaders have consistent insight into what is happening in the here-and-now, they can empower every application to meet the end-user with instantaneous action. Such real-time analytics captures information as it happens, removes silos, and creates strategic intelligence tied to vital changes or events, as frequently as data teams require.
But this potential of real-time data is yet to be harnessed fully. According to a recent McKinsey study, only a fraction of data from connected devices is processed and queried in real-time, due to the challenges of adopting modern data architectures. These challenges can be resolved by harnessing data at rest in the database and data in motion in advanced streaming technologies and bringing it together for use across the entire organization and applications in real-time.
By activating data in real-time, customers and companies can get smarter together, while enterprises deliver exceptional, up-to-date digital experiences. Having access to high computational intensity available in the cloud, which is serverless, empowers developers to quickly build innovative and game-changing applications while delivering speed, scalability, and availability at a fraction of the cost.
The views in this article is that of the author and may not represent the views of Tech Wire Asia.
- Adobe’s Achilles heel: How InDesign became a hacker tool and what other options are out there
- Unprecedented data breaches of the last ten years – and their aftermath
- Adobe products continuously targeted for phishing attacks
- Singapore’s AI strategy 2.0 explained
- Can AMD disrupt Nvidia’s AI reign with its latest MI300 chips?