“It Was the Best of Times, It Was the Worst of Times” – Charles Dickens
The first 12 words in Charles Dickens’ classic A Tale of Two Cities captures the opportunity and challenge that organizations face when attempting to bring together data-in-motion and data-at-rest.
The opportunity is business transformation driven by data. Engaging and delighting customers, optimizing operations, and accelerating innovation to name a few.
Two Cities at a Glance
On the other hand, the challenges are myriad. In my experience, the teams and technologies used to manage and get value from data-in-motion, typically housed in Operational Technology teams deployed within lines of business such as financial trading, logistics, and manufacturing are distinct from their data-at-rest specialist tools and colleagues in Information Technology and Analytics teams.
Streaming technology successfully addresses capturing massive volumes of device-collected data-in-motion, rapidly understanding the hundreds of machine-driven protocols involved and transforming it into intelligent actions with the goal of optimizing the moment. On the other side of the coin, data management technology successfully addresses the massive volumes of at-rest transactional data, transforming it into insights that drive better business results in the future.
Is there a Case for Combining Data-in-Motion and Data-at-Rest?
Since both data-in-motion and data-at-rest have value on their own, are there one plus one equals three opportunities when combining the two? The answer is most certainly yes and here are just a few examples:
- Financial trading risk management – Combining real-time trades with current positions data provides risk managers with a broader view of portfolio risk.
- Route optimization – Combining real-time location, traffic, and weather feeds with truck and driver capabilities and manifest data enables dispatchers to optimize their fleet’s performance.
- Predictive maintenance – Combining real-time machine diagnostics data with maintenance histories, repair team schedules, and more helps process engineers maximize uptime and yields.
Phil Unger, CEO at TIBCO Partner Cadeon, a Calgary based system integrator specializing in the energy industry, believes this combination will prove extremely valuable to his clients. “We currently have both large Oil & Gas clients as well as small, yet highly successful drilling services clients who use TIBCO Data Virtualization to integrate their data-at-rest. They will be pleased to hear that in the latest release, TIBCO added a native streaming data function that will simplify how they ingest, integrate, and deliver their mix of in-motion and at-rest data. It will help the producers raise yields and reduce both operating and IT costs. And for the services firms, it will accelerate their time-to-market for new data-driven services.”
“It Was the Age of Wisdom”
Given the breadth and impact from these in-motion and at-rest combinations, the question becomes how can one do it effectively? The next six words from Dickens, “it was the age of wisdom,” guide us to look toward technical innovation for that answer.
With TIBCO Data Virtualization 8.3, TIBCO recently announced a breakthrough set of capabilities for easily combining data-in-motion and data-at-rest.Streaming technology addresses capturing massive volumes of device-collected data-in-motion, rapidly understanding the hundreds of machine-driven protocols involved and transforming it into intelligent actions to optimize the moment. Click To Tweet
Also available is a new white paper, Introducing Data Virtualization for Streaming Data: Virtualize data at rest and data in motion, that I co-authored with TIBCO’s Mark Palmer and Stephen Archut. This paper provides additional wisdom on what, why, and how to bring together these two cities.