IT Briefcase Exclusive Interview: Streaming Data Automation and the Internet of Things (IoT)
The emergence of The Internet of Things (IoT) has created frenzied excitement for the technology industry because it heralds the leap from technology being something that supports our modern lifestyle to something that pervades our modern lifestyle. And with this shift comes a huge commercial opportunity. Gartner research says there will be 20 billion IoT devices by 2020, with the IoT economic value expected to reach $11.1 trillion by 2025. It’s a new Gold Rush.
But just like the Gold Rush where everyone ran towards the Gold and forgot that fortunes could be made from supplying tools to prospect with, many companies today are only focused on what they can ‘do’ with the data and are neglecting to plan how to store and manage all this new data. And as such, they could be in for a shock when they come to try and realize the potential that IoT brings. WhereScape’s CTO Neil Barton, explains why data streaming automation is essential if companies want to really embrace (and exploit) the IoT revolution.
Q. Why does streaming data matter in the Internet of Things (IoT)?
Put simply, the sheer volume of data that is being generated and consumed in IoT today can be overwhelming without the infrastructure in place to manage it. Additionally, being able to analyze the data as close to the time it was generated can have significant benefit to a business. The only way to realistically process and analyze this data is on a streaming basis from devices out in the field as soon as it is created, not at a point in time in the future.
Let me give you a real-world example – imagine a bus company that has hundreds of buses on the road every day. The company wants to understand, as close to real time as possible, how its fleet of buses is performing so that it can maximize the efficiency and reliability of its service. Now, with data captured from on-board sensors, the bus company can analyze that data in real-time, allowing it to diagnose and detect problems immediately.But, historically, data was downloaded from sensors at the end of the day, which proved limiting, because the bus could have broken down earlier in the day or could have been behind schedule all day, and there would be no way to get ahead of the problem.
However, with streaming data, if a bus was in danger of breaking down, the problem could be detected by analyzing the sensor data as it is produced and then steps could be taken to prevent it. By processing data in real-time, the bus company could identify immediately if, say, the engine temperature was outside of historical norms and therefore recommend the bus be brought in for service, before it could break down.
Q. OK, so how can business cope with the deluge of data created by the emergence of IoT?
The simple answer is that automation of the data management process must be a given – it saves time, reduces costs and prevents risk – all things that drive competitive edge for businesses. So, as people are creating large quantities of data, automating the data ingestion process can drastically improve the quality and reliability of the results.
Automation reduces the need for human interaction by eliminating the hand-coding and repetitive, time-intensive aspects of data infrastructure projects. This then means two things. First that insights from the data can be delivered in days, rather than months or years. And second, by freeing up humans to concentrate on the more strategic work of analysis and data output, you can deliver richer insights back to the business.
Q. Where do you see the IoT market headed in the future?
IoT is fast becoming mainstream. It’s no longer limited to big enterprises with large budgets because ‘in the field sensors’ are becoming so cost affordable now. Companies of all sizes, should be looking to take advantage of the information stream IoT can provide. And additionally, the cost effectiveness and quick ‘time to value’ offered by streaming data automation tools to any size of business to enable access to technology, data and insights that can create immediate value.
From here, businesses will then start to incorporate artificial intelligence, deep learning and machine learning into their organizations to further manage and derive value from their data. This trend will continue to grow and evolve in the coming years. We will then see the limit of what people do with data no longer come from their ability to afford the technology to harness it but, instead, from their creative application of the insights that they are able to create on a continuous basis.
For more information on IoT and automation for real-time data streaming, visit WhereScape, the leading provider of data infrastructure automation software.
About the Author
Neil Barton is the CTO for WhereScape, the leading provider of data infrastructure automation software, where he leads the long-term architecture and technology vision for the company’s software products. Barton has held a variety of roles over the past 20 years, including positions at Oracle Australia and Sequent Computer Systems, focused on Software Architecture, Data Warehousing and Business Intelligence. Barton is a co-inventor of three US patents related to Business Intelligence software solutions.