Like many industries, the energy sector is undergoing widespread digital transformation. As more power and utility providers adopt artificial intelligence, IoT, and other smart technology to support their business lifecycles, data analytics is becoming an essential part of managing the modern energy infrastructure.
But analytics alone can’t provide the insight needed to drive action. Organizations must take their data and present it in a way that is both understandable and usable to everyone, not just data scientists.
Data visualization bridges this gap and helps the energy sector embrace digital transformation by redefining how businesses, stakeholders, and customers are able to use their data to meet their respective end goals.
What Is Data Visualization?
Traditional data analytics rely on flat, two-dimensional data representations and provide limited insight into the real relationships within an organization’s structured and unstructured data.
Today’s data visualization tools, however, take that structured and unstructured data from multiple sources and compile it into a visual representation that can be used to tell your data’s story in a clear, concise, and easy-to-understand way.
Data visualization makes it possible to determine which variables have the greatest impact on the target data, as well as pinpoint trends, patterns, and outliers in the data. This information can then be used to drive decision-making, increase efficiency, and predict performance problems before they become big, expensive issues.
How Data Visualization Is Driving Change in Today’s Energy Sector
In the energy sector, data visualization enables a wide variety of use cases, but there are five areas in particular where taking a visual approach to understanding data insights has a huge impact:
1. Forecasting Load and Demand
In the energy sector, businesses expend a lot of effort trying to match available power supply with energy demand. Data analytics is an essential part of this load management and demand forecasting process, but it must be done well to be valuable.
Poor-quality data or lack of visibility into trends makes it difficult to accurately predict actual needs, leading to wasted resources and unhappy customers. Data visualization provides in-depth insight into past usage and demand levels, allowing energy providers to make informed projections based on actual data trends.
2. Isolating the Root Cause of Performance Issues
Data analytics may be able to show that a performance problem exists, but it doesn’t provide the “why” behind the issue. Although it is important to identify broken systems and components, if operators can’t determine the root cause, it’s likely that the issue will reoccur.
Data visualizations incorporate data from multiple sources and provide insight into which variables are likely contributing to breakdowns and inefficiencies. Using this “whole picture” approach to pinpointing performance issues helps minimize the amount of time maintenance teams spend looking for the cause so they can make repairs quickly and prevent reoccurrence.
3. Predicting Equipment Failures And Maintenance
Unplanned downtime and unscheduled maintenance cost companies both time and money.
AI routines and machine learning can be used to create data visualizations that accurately predict which systems are likely to fail and when. This information can be used to schedule proactive maintenance and replacement of at-risk components to reduce downtime and prevent outages.
4. Improving Stakeholder Communication
Not every stakeholder and decision maker in an organization is a data scientist, but they still need to be able to understand and explain to others what the data is showing. Energy and utility companies tend to have multiple sites distributed across a wide region, which makes efficient communication and collaboration even more important.
Data visualization allows even non-data professionals to easily extract actionable insight from data, then use the visualizations to engage and inform other team members across geographies.
5. Increasing Customer Satisfaction
Smart metering allows energy and utility companies to collect customer data from multiple sources, which allows them to closely analyze customer behavior and resource usage.
This data can be combined with additional metrics, such as weather patterns and time, then used to create a multidimensional visualization that allows analysts to examine the data from many angles. This level of visibility helps the utility company identify inefficiencies, provide more targeted customer service, set customer expectations based on real data, and resolve issues faster.
Many industries are undergoing rapid digital transformation, but the energy sector in particular is poised to see huge returns on its data analytics technology investments. Data visualization helps energy and utility providers quickly identify where they can improve process, productivity, and maintenance efficiencies with high ROI potential.
Find out more about how the energy sector benefits from new data analytics and visualization techniques on our comprehensive page, Data Visualization in the Energy Industry.
Understanding consumer behavior patterns can be difficult because of the high volume of data that companies gather. Making sense of it requires sophisticated analysis tools. Many companies rely on traditional analysis, which is two-dimensional (2D) and can only explore limited variables. To drive better decision-making in customer segmentation, three-dimensional (3D) data visualization supported by AI allows you to uncover much more.
For a glimpse of how it works and to support the points below, take a look at this video of how 3D data visualization works.
Why Does Understanding Consumer Behavior Patterns Matter?
Any business wants to spend its marketing dollars wisely. Creating campaigns that are general in nature likely won’t deliver high revenue. Instead, you want to target as precisely as possible based on your customers’ buying activities.
We can all agree that consumer behavior patterns are shifting and changing. Many things impact these patterns, both internally and externally. The last year-plus shifted the consumer base tremendously. For example, 75 percent of consumers tried new brands and different ways of shopping since the beginning of the pandemic.
Consumer behavior is a “live” data set, and deriving insights from it needs to happen quickly, so you can pivot to align with current motivations.
Identifying Influences on Buyer Behavior Allows You to Personalize Promotions
If you can identify what influences consumers’ buying decisions, you can deliver more relevant content and promotions to them. For example, you may want to know how consumers decide which product to purchase. There will be many avenues they take, but you can use 3D data visualization to find patterns. Do most shoppers look at 10 products before purchasing? What do they click on when evaluating a product—the details, pricing, reviews?
Further, you can determine what products customers keep passing up. This information can save you from wasting money on promoting a product that’s not a hit. You can also look at more nuanced patterns and try to discern correlations.
So how do you get to these realizations? Elevating your analysis from 2D to 3D is critical.
2D Visualization Leaves Question Unanswered
Consider 2D to be the starter data science equation. You can see some probable insights, but there are limitations when it comes to discovering more complex relationships within the data. Occlusion is a common challenge, meaning that some data points are hidden behind others. And what’s hidden isn’t actionable.
Going to the demonstration in the video above, you’ll notice the 2D graph doesn’t provide you with enough information to uncover the answer to the question of what drives the amount spent. But when you apply AI tools and 3D visualization, the data behind spend becomes more accessible. You can add new dimensions of X, Y, Z, and color.
By using 3D visualization versus 2D, you learn much more that wasn’t obvious before. The findings in the data set defined two specific segments and how and why they spend more. With this knowledge, you can create more tailored marketing to these groups that resonate with them and prompt them to buy more.
AI Routines and 3D Data Visualization Make Data Actionable
Large volumes of data can’t contribute to better decision-making without analysis, and analysis involves a tremendous amount of processing power and data science. Because consumer behavior data is constantly changing and growing, you need fast analysis to take action. That’s the value of using AI routines and 3D data visualization.
With AI routines, you can set a target feature to better understand, such as the example in the video. You’re looking for the “why” behind spending. Any hypothesis around this is just that—a theory—until data fills in the gaps. By adding variables to the target, you can see how they impact that target feature. AI helps you connect the dots, delivering the variables that most impact the question behind spend amounts.
Because of the 3D data visualization, you can see the “why” clearly as you manipulate the data. It’s there on the screen with color and point size. When you find these insights, they contribute to what you do next for your customer base. Those behaviors that correlate to the question at hand, which AI identifies as important, are also viewable in histograms. Having this capability offers ideal segmentation among your customer base.
AI Drives More Actionable Data to Better Understand Consumers
Data-driven decisions are usually smarter than other decisions. You likely have lots of customer data—but is it improving your ability to understand consumer behavior? Are you finding patterns that help you segment and target better? That’s achievable with AI and 3D data visualization through the Virtualitics AI Platform. This accessible technology enables insights into complex data discoverable with a click.
Data is used throughout the organization—from marketing and HR to IT and inventory management—so data analysis results need to be easy for anyone to understand.
The primary purpose of data analytics is to find information that is hidden within the data and then use that information to drive some sort of action. But, often, the data—and the information pulled from it—is complex. It can be difficult to convey the actionable information to stakeholders and decision makers, who in all likelihood don’t have a background in data science.
Data visualization is frequently used as a tool to bridge that gap between analysis and understanding by translating information into a visual context that makes data easier for the human brain to make sense of.
The Benefits of Data Visualization in Data Analytics
Data visualizations take complex, multi-source data and compile it into an easy-to-understand representation that clearly defines the most important and relevant information. Visualizations make it easier to identify patterns, trends, and outliers in large data sets, which helps draw out useful insights that otherwise would remain hidden.
When data is presented visually, especially three-dimensionally, these insights can be absorbed more quickly, which helps speed up decision-making and drive data-based action.
Data visualizations also simplify collaboration across geographies. Team members and stakeholders can explore and analyze data visualizations together in real time, no matter where they are located.
3 Ways Visualizations Find Efficiencies
Many industries—including manufacturing, energy, natural resources, aerospace, telecommunications, and transportation and logistics—use data visualizations to find efficiencies in their processes. Visualizations help organizations get the maximum value from their data analytics efforts and use the information to make better decisions and improve business outcomes.
Here are a few examples of how data visualizations help businesses find efficiencies in three very different industries.
1. Process Improvement
The logistics industry ensures essential goods are delivered to the right place on time and on budget.
One way logistics teams accomplish this is by determining the most efficient routes for delivery drivers, so the business saves time, money, and fuel. Calculating savings and efficiencies based on route is practically impossible to do “in the wild,” which is where data visualizations come in.
Data analysts incorporate data from disparate sources, such as mileage logs, fuel sensors, and GPS, to create a 3D visualization that not only shows the most efficient options but also allows business stakeholders to manipulate variables to measure their impact on the target data.
2. Performance Monitoring
In this example, a sustainable energy provider is looking for the root cause of frequent equipment failures. In order to do so, the provider needs to be able to monitor and quickly analyze sensor data to determine the condition and performance of its equipment.
Visualizations let this organization analyze sensor data from its wind turbines to quickly characterize why the equipment might be behaving a certain way. By adjusting the variables shown in the visualization to have the greatest impact on the target, the energy provider is able to pinpoint the cause of the failure and resolve the issue.
3. Predictive Maintenance
Fleet maintenance is a prime use case for data visualization. Artificial intelligence-driven predictive models can be used to identify parts or systems at risk of failing. This information is then used to alert maintenance teams of potential issues so they can take proactive maintenance action and minimize downtime.
Data analysis and visualization tools can also be integrated into automated inventory systems. This allows maintenance teams to keep track of which parts fail most frequently so they can always have those parts in stock when they are needed.
Use Visualizations to Supercharge Your Data Analytics
Data visualization is a fast and efficient method of communicating complex information in a universally understood way.
Using multi-dimensional visualizations and 3D digital objects, you can connect your entire ecosystem of data and personnel to improve understanding of data, alerts, and predictive models.
Visualizations help uncover process efficiencies in every industry by ensuring that the right people in the organization can easily monitor the performance of critical systems and fully understand what the data is telling them. Armed with this knowledge, stakeholders can make process and policy improvements that benefit business outcomes.
Data is a valuable commodity in today’s information-driven business environment. But, unlike currency or other assets, data’s real value is in the actionable insight you extract from it.
Data analytics has become much more challenging in recent years with the volume of data being generated skyrocketing to trillions of rows per day, much of it unstructured. To further complicate matters, data is delivered from many different sources, which creates multidimensional data sets that must be carefully analyzed to identify patterns and interrelationships among the disparate data types.
The Role of Visualization in Data Analytics
The human brain does many things well, but scaling isn’t one of them. To help simplify analysis and maximize value from high volumes of increasingly complex data, more organizations are relying on data visualization technology to make sense of it all.
Data visualization—which, at a high level, is simply the visual representation of information—drives data analysis by removing the noise and presenting data in a way that is easily internalized.
Unlike using a spreadsheet filled with numbers and no context, telling your data’s story in a visual form clearly highlights trends, patterns, and outliers within the data set so the most useful information is front and center.
This visual approach also adds “explainability” to complex concepts that non-data-scientists, such as product owners and management, need to drive decision-making and meet business objectives.
The Era of Immersive Data Virtualization
In today’s highly complex business environments, static visualization is no longer sufficient in the majority of use cases. Extracting the most valuable data insights requires multidimensional, immersive visualizations so users can really drill down and interact with the data, looking at it from every angle.
By expanding data analytics capabilities beyond static visualization and basic interactivity, immersive data virtualization provides AI-driven data analytics and 3D visualizations that let anyone in the organization—not just the data scientists—get fast, actionable insights from even the most complex data.
Immersive visualization platforms give data-centric organizations the ability to view data in a variety of geospatial, 3D, and graphical visualizations, which makes it easier to spot anomalies and patterns in the data and pull out important information and trends even from unstructured data.
Pain Points Solved with Immersive Data Visualization
Immersive data visualization creates highly informative yet easy-to-understand data representations that help organizations overcome several key business challenges:
Siloed Operational Knowledge
Immersive data visualization makes even the most complex data accessible to the masses. Non-data-scientists can generate and manipulate data representations themselves to extract business-critical knowledge that drives decision-making.
Collaboration Among Distributed Teams
Immersive data visualization platforms let teams share insights and collaborate on actionable information across the office or across the globe.
Missed Growth Opportunities
Immersive data visualization presents data clearly and concisely, making it easy to spot trends and anomalies that highlight areas for improved efficiency and opportunities for increased market share.
Finding the “Whys”
It isn’t always clear what is triggering sensor or system alerts, and this lack of clarity can result in alert fatigue and increase risk. Immersive data visualization lets users track alerts and visualize the data from multiple angles to pinpoint the root cause and quickly resolve issues.
Connecting the Dots Within Data Relationships
Enterprise data comes from a million different directions at once. Immersive data visualization takes these disparate data types and sources and creates a clear, cohesive picture of the data’s story across them all.
Immersive Data Visualization and the Human Element
The human brain is designed to navigate a 3D world, which is why we can grasp concepts such as the size of objects and relative distances between points.
Although static visualization techniques such as bar charts and 2D scatter points are somewhat useful for understanding data, today’s complex data sets demand multidimensional visualization and interaction.
Immersive data visualization technology allows users to create robust, collaborative environments where they can explore different dimensions of the data to tell a story everyone can understand and build on.
Bryant’s new Data Visualization (DV) Lab is equipped with state-of-the-art virtual reality (VR) and data visualization technology and provides access to fully-immersive experiences for students and faculty across the University. After opening in April 2019 through a generous gift from HP, the DV Lab’s innovative, multidisciplinary technology is helping prepare the next generation of leaders to take their place at the forefront of a technology-driven future.
“The DV Lab is forging a “new frontier” for Bryant, one that takes a lot of collaboration and teamwork to explore and use to its potential,” says Philip Lombardi, Director of Academic Computing and Media Services.
Bryant’s innovative academic programs and transformative learning experiences – including the DV Lab – are among the reasons why the University was recognized by U.S. News & World Report as the No. 8 Most Innovative School in the 2020 College Rankings.
Exploring the nearly infinite possibilities
The possibilities for how the DV Lab’s technologies and capabilities can be used are as boundless as the imaginations of the interdisciplinary faculty and students who are using the space.
“Our new Data Visualization Lab will enhance learning for all of Bryant’s students—and we are only beginning to imagine the myriad ways that we can use this technology in our College of Business, our College of Arts and Sciences, and our Physician Assistant program.”
“Our new Data Visualization Lab will enhance learning for all of Bryant’s students—and we are only beginning to imagine the myriad ways that we can use this technology in our College of Business, our College of Arts and Sciences, and our Physician Assistant program,” says Provost and Chief Academic Officer Glenn Sulmasy, J.D., LL.M. “The possibilities are as exciting as they are numerous.”
Sulmasy appointed a Provost Technology Advisory Group in 2018 to anticipate future technology trends and determine how to best incorporate them on campus. The group includes co-chairs Ed Kairiss, Ph.D., Director of Faculty Development and Innovation and Director of the new Center for Teaching Excellence, and Philip Lombardi, in addition to faculty representatives from both the College of Business and College of Arts and Sciences.
Sulmasy, Kairiss, and Lombardi meet with Chuck LoCurto, Vice President for Information Services and Chief Information Officer, and David Gannon, Director of Campus Technology Services, on a monthly basis to discuss high-level strategic technology planning for Academic Affairs.
“If you wait until you have all the answers, you’ll never do it, because as fast as you add it in, the technology is changing.”
Bryant also partners with industry leaders to stay ahead of the latest trends, but the key is to act fast. “If you wait until you have all the answers, you’ll never do it, because as fast as you add it in, the technology is changing,” states LoCurto.
From time travel to 3D prototyping
Bryant faculty recognize the potential of the lab’s immersive, multidisciplinary experiences and are exploring paths to integrate the technology into their classroom. Some programs and applications are well underway.
Ryan Marnane, Ph.D., English and Cultural Studies Lecturer, uses the DV Lab’s technology to enable time travel for his Introduction to Literary Studies students. Using Windows Mixed Reality headsets and controllers, students travel back to Abraham Lincoln’s time, though a VR adaptation of George Saunders’ novel, “Lincoln in the Bardo.”
Allison Butler, Ph.D., Professor of Psychology and Director of the IDEA (Innovation and Design Experience for All) Program, and Lori Coakley, Ph.D., Professor of Management, secured a Faculty Innovation Grant that will fund intensive training using VR technology in the DV Lab. This will enable students in the “Psychology/Management 440: The Design Thinking Process” class to develop and iterate concepts using 3D prototyping in addition to the traditional manual prototype building methods.
David Louton, Ph.D., Professor of Finance, is currently experimenting in the DV Lab with Virtualitics, a state-of-the-art data analytics platform, to investigate market data – and discover patterns – that are not easily recognizable in 2D formats.
“More innovative, more practical, and more efficient”
“We try to help [the Bryant community] apply the new technology, so that they can be more innovative, more practical, and more efficient in what they do,” says Lombardi.
Bryant’s DV Lab will be applied to nearly every course of study, creating access to technology that can spark innovation for both students and faculty. “Other campuses are excited about our multidisciplinary approach because it goes beyond data sciences to encompass a broad range of fields such as Biology, Chemistry, Communications, and Applied Psychology,” adds Lombardi. “What makes us different is our variety of uses.”
“The DV Lab also offers interdisciplinary possibilities for faculty to work together,” says Kairiss. “For example, in Marketing a lot depends on how humans focus their attention and respond to stimuli such as product placement – which is also a concern of Psychology.” This technology has a world of potential in empowering students to examine subject matter in a new and exciting way.
Additional upgrades to academic technology on campus
Bryant’s “new frontier” of technology innovations goes beyond the DV Lab. The University is committed to anticipating and adapting to future technology trends and continues to upgrade and integrate new academic technology across its campus. Some of the latest innovations include:
- added/upgraded technologies in the TV Studio to accommodate new program offerings
- upgraded the Psychology Lab, now called the Behavioral Lab, with technology to assistant with interviews and analysis
- purchased NAO, the humanoid robot, for in-classroom use
- added wireless projection in many classrooms and conference spaces
- upgraded the Virtual Desktop infrastructure to support high-performance computing needs for Data Sciences
- added two new large video walls in the Quinlan/Brown Academic Innovation Center Forum
- upgraded the technologies in Janikies Theatre, the Rotunda, athletic spaces, and some residence halls
- upgraded incoming freshmen and junior laptops to higher performance devices
- in the process of adding web conferencing in student group study rooms
Through the DV Lab, Bryant continues to evolve and innovate to ensure its students are prepared for the world and workplaces they will encounter when they graduate.
Published by Bryant University: https://news.bryant.edu/data-visualization-lab-opens-new-frontier-bryant
The FinTech Innovation Lab was co-founded by the Partnership Fund for New York City and Accenture in 2010.
Our time at the FinTech Lab was invaluable, helping us to hone our product to be a vital tool not only for financial services but for any company’s infrastructure. Watching this video is a great introduction to Virtualitics, but we agree with Ari Koban from BlackRock when he encourages “all of you to go after this, put a headset on and see what it has to offer, and experience what you can learn in this VR environment because it’s incredibly impressive!”.
Watch how our CEO, Michael Amori, addressed the audience on Demo Day in late June 2018 and shared all of this and more.
SXSW Pitch is the marquee event of South by Southwest® (SXSW®) Conference & Festivals (March 13 – 22, 2020) Startups Track, where leading startups from around the world showcase some of the most impressive technology innovations to a panel of hand-picked judges and a live audience. Out of the 937 companies that applied to present at SXSW Pitch 2020, Virtualitics was selected among the 50 finalists spanning 10 separate categories.
The two-day event will be held the first weekend of SXSW Conference & Festivals, Saturday, March 14 and Sunday, March 15, on the fourth floor of the Downtown Hilton Austin, Salon D/E. The event will then culminate with the 2020 SXSW Pitch Awards Ceremony on Sunday evening, March 15, where winning startups from each category and a Best in Show winner will be announced and honored.
SXSW Pitch will feature finalists across the following 10 categories: Artificial Intelligence, Robotics & Voice, Augmented & Virtual Reality, Blockchain, Consumer Technology & CPG, Enterprise & Smart Data, Entertainment & Content, Health, Wearables & Wellbeing, Innovative World Technologies, Smart Cities, Transportation & Logistics, and Social & Culture.Virtualitics will present among four other companies in the Enterprise & Smart Data category on March 14th, 2020.
According to Ciro Donalek, CTO and co-founder of Virtualitics: “Our mission is to democratize machine learning, to allow anyone, regardless of their background quickly get insights from complex data. Lack of data scientists and the inability for standard BI tools to keep up with the new data challenges are crucial pain points in being able to extract value from the huge amount of data available nowadays. That’s where our solution has shined, helping our clients to understand their data and achieve actionable insights quickly. For over a decade, SXSW Pitch has played a pivotal role in shaping the early-stage venture ecosystem, giving promising companies the resources they need to succeed when it matters most and providing high profile exposure through judges from key industry players such as Amazon and Google X,” said SXSW Pitch Event Producer Chris Valentine. “Of the 503 companies who have participated since the competition’s inception, over 75 percent have gone on to secure funding and 16 percent have been acquired. We’re excited to see this year’s impressive group of startups take to the stage and show us how their innovations will change the world.”
For more information about SXSW Pitch and to view the complete list of finalists, visit: https://www.sxsw.com/pitch
About Virtualitics
Virtualitics, Inc. is a data analytics and visualization company based in Pasadena, California that merges artificial intelligence and virtual reality to gain intuitive insights from big and complex data. Its flagship product, Virtualitics AI Platform, is a state-of-the-art data analytics platform available to enterprise customers in both desktop and VR. It enables enterprises to easily uncover key actionable insights in their data through a combination of machine learning and advanced visualization. The patented technology is based on a decade of research at the California Institute of Technology and NASA’s Jet Propulsion Laboratory (JPL).
Virtualitics also offers expert advisory services in machine learning, boasting a team of Caltech-trained data scientists, skilled software engineers, designers, and UX specialists. Included among the company’s clients are Moody’s, Daimler, Assembly Agency, U.S. Department of Defense, Nestle, University of Southern California and more.
For more information and to request a free trial, please visit www.virtualitics.com.
About SXSW
SXSW dedicates itself to helping creative people achieve their goals. Founded in 1987 in Austin, Texas, SXSW is best known for its conference and festivals that celebrate the convergence of the interactive, film, and music industries. An essential destination for global professionals, the event features sessions, showcases, screenings, exhibitions, and a variety of networking opportunities. SXSW proves that the most unexpected discoveries happen when diverse topics and people come together. SXSW 2020 will take place March 13 – 22, 2020. For more information, please visit sxsw.com.