Three Technology Trends and Their Effects on Data and Software

Companies using OSIsoft’s PI System gathered this week in London at the OSIsoft EMEA Users Conference to talk about the realities of what Martin Otterson calls the velocity, variety and volume of data in the modern business world.

Otterson, who is OSIsoft’s senior vice president of customer success, said during the welcome session on Tuesday, for example, that Detroit-based DTE Energy manages 27 million data tags, or datapoints that hold a single value over time. And renewables company E.ON manages data that comes in 250 formats.

OSIsoft’s PI System allows organizations to collect, analyze and visualize large amounts of data from multiple sources. 

The new data challenge, Otterson said, is to build on the current business architecture to develop new business practices for changing markets and understand how businesses can respond to those changes quickly, and survive.

During the welcome session, Ronan de Hooge, OSIsoft’s chief software architect, identified three technology trends that are driving business data and how software is responding to better use that data for growth.

More Data from Sensing Technologies

Since 2008, IoT connected devices and sensors have increased by 4 billion, and by 2020 they are expected to reach 20 billion, according to de Hooge.

“That means there is a lot more data out there,” he said, adding that there are many different ownership rules for that data and it arrives at different frequencies.

In the business world, data will be coming from traditional control systems, directly from sensors into the cloud, and from external clouds.

De Hooge said that software will begin to help organizations bring all that data into one system, then contextualize it and give it a structure that can drive organizational decision making.

More Storage and Computing Capacity

According to de Hooge, base computing platforms are seeing an increase in capabilities in terms of storage and raw computing capacity.

He said that by 2030, mobile devices are expected to have 60 petabytes of data storage, where one petabyte represents about 200,000 DVDs.

He also said that the powerful computing systems we’re seeing today can bring machine learning and artificial intelligence into the forefront of organizational strategies.

“What they’re expecting is that you’ll start to see systems that can, for example, perform operations that produce highly accurate weather forecasting,” he said.

Software will begin to respond to the increase in storage and computing capacity by reshaping that data, de Hooge said.

In addition, software designers will work to structure data so that organizations can use it to create meaningful insights, and expose data to artificial intelligence and machine learning.

The ultimate goal, he said, is to make sure that data is timely and shaped, and it’s ready for the decision-making process.

More Action from Insights

According to de Hooge, the value of the insights gained from data will come from what organizations do with those insights.

He said that the human-based interaction models, such as virtual reality systems and digital assistants — think Alexa and Google Home — that are beginning to enter the commercial market will spill over to the industrial sector in the next few years. Organizations will begin to take advantage of these systems in the work environment to drive strategy.

In addition, more organizations will place their trust in machine-based automation for decision making, he said. The technologies behind, for example, blind spot detection and crash avoidance in cars, will make their way to organizational processes as decision makers learn to trust artificial intelligence and machine learning.

“When you start to institutionalize information and patterns at the automation level,” de Hooge said, we’ll see decision makers step away from the controls and let the systems make the decision for them.

Software will begin to respond to the need for systems that can support those interaction models for the organizations that seek to implement them.

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Jennifer Delony, analyst for TransmissionHub, started her career as a B2B news editor in the local and long-distance telecommunications industries in the '90s. Jennifer began covering renewable energy issues at the local level in 2005 and covered U.S. and Canadian utility-scale wind energy as editor of North American Windpower magazine from 2006-2009. She also provides analysis for the oil and natural gas sectors as editor of Oilman Magazine.

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