Ultimate Guide to Building Analytics: Making Big Data Approachable

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Human brains are extraordinary organs. Able to think both imaginatively and analytically, our brains continuously synthesize information to solve problems and make decisions. Through experience, we can determine how and why events happen, and we even use historical knowledge to predict what is likely to occur in the future.

Building analytics with machine learning (ML) capabilities uses these same processes to understand and correct issues within the built environment. Today, savvy building owners are using this powerful technology to harness big data and unlock the full potential of their properties.

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What Is Building Analytics?

Building analytics software evaluates real-time and historical data collected from building equipment, sensors, and devices. These technologies use this data to find patterns, identify anomalies, and predict future events. Working in tandem with a building automation system (BAS), the best analytics platforms learn how to resolve problems and achieve specific goals. The greatest benefits are realized in integrated smart buildings with seamless data flow.

What Is Big Data?

The concept of “big data” emerged in the mid-1990s, as the volume of data increased exponentially with the growing use of computers and the Internet. So what exactly is big data?

Big data has five defining characteristics:

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Volume:

Though there is no minimum size associated with big data, it typically involves an amount of a terabyte or more.

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Variety:

Big data includes many different types of data that are stored and processed on the same system.

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Velocity:

Datasets include real-time data like that generated by IoT sensors, which are rapidly updated.

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Veracity:

It’s critical to appraise the accuracy of such large datasets.

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Value:

Establishing the significance of collected data allows it to be used the most effectively.

Variability is also an important factor, as big data typically appears in multiple formats depending on the source system.

Significantly, big data is too big to be handled by humans alone. Making big data useful requires advanced technology to organize and prioritize data and draw out meaningful insights.

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How Big Data Relates to Building Analytics

In the 2000s, the introduction of open-source structures to store data and run applications for off-the-shelf hardware, including IoT devices, brought big data to a whole new level. Such platforms provided the enormous processing power needed for smart automation within built environments, and the ability to store massive amounts of data allowed systems to handle a wider array of tasks while increasing efficiency in operations. They also allowed for the analysis of building data in much the same way as search engines and online indexes are used to find relevant information online.

Today, cloud-based platforms for big data offer:

  • Quick storage and processing.
  • Better scalability of smart building systems.
  • Flexibility in the type and amount of data stored.
  • Lower data storage and system set-up costs.
  • Protection of data against hardware failure.

The capabilities of these platforms are continuously advancing, bringing even more speed and agility to building analytics.

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The Benefits of Building Analytics

Data analytics software designed specifically for the built environments is the key to unlocking the potential of smart building technology. Not only do building analytics show what is happening in a building, it also helps explain why it is happening and what is likely to happen in the future. This has major operational and capital benefits.

  • Allows for advanced automation.
  • Increases energy efficiency.
  • Monitors systems in real-time to identify faults and waste.
  • Streamlines maintenance.
  • Increases lease and sale prices.
  • Improves occupant comfort.
  • Predicts future energy use.
  • Allows more informed decision-making.
  • Reduces overall costs of building operations.
  • Extends the useful life of equipment and systems.

The combined use of building analytics and big data allows building owners and operators to fully capitalize on their automated systems. However, most use a very limited portion of the potential that their BAS offers. This is often due to a lack of training on such software platforms. Choosing intuitive, user-friendly platforms or using a smart buildings expert to oversee BAS operations are easy ways to overcome such challenges and get the most out of an analytics-driven BAS.

Turning Insight Into Action

Building analytics platforms act like interpreters, translating the language of a building’s systems to help stakeholders understand the meaning behind building data. Yet the true value of big data and analytics isn’t just insight—it’s the ability to drive action.

Actionable insights are those that drive change and help to produce positive outcomes for stakeholders, whether they be building owners, facility managers, maintenance crews, or tenants. Actionable insights should ideally have all of the following attributes:

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Applicability:

The actionability of an insight depends on who the audience is. For example, it does no real good for the cleaning staff to understand why an elevator in a building is not operational, as they don’t have the ability to fix it.

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Context:

You must understand underlying circumstances so that insights answer questions rather than create new ones. For example, seeing a dramatic increase in HVAC use in July is expected and does not necessarily indicate a problem.

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Distinctiveness:

Insights that bring to light new information or patterns are more likely to result in action. If IoT sensors detect a sudden spike in particulate matter, for example, action is very likely needed to protect air quality.

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Precision:

The more specific an insight, the more actionable it is. An anomaly detected by the building analytics platform may indicate a problem, but without sufficient information it cannot be acted upon. With further investigation, however, it can become actionable.

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Purpose:

Those insights that align with the objectives of building owners and other stakeholders are more likely to be acted upon.

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Simplicity:

Stakeholders need to be able to understand the insight. To facilitate this, building analytics platforms should offer data visualization and other user-friendly ways of presenting data.

Choosing analytics software with the ability to produce such insights is invaluable for getting the most out of big data.

But the best analytics software doesn’t stop at actionable insights; it defines the actions that should be taken. That means recommending solutions to problems so you can implement meaningful change.

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onPoint Analytics

onPoint is an innovative analytics platform that gives you extraordinary insight and control of your property.

  • 4-D insights: onPoint uses real-time and historical data to understand what is happening in your building and help identify the root causes of alerts.
  • Mobile access: The ability to view actionable insights via smartphones, laptops, tablets, or other connected devices helps you stay agile and responsive.
  • Predictive: onPoint uses advanced machine learning algorithms to make accurate predictions and empower you to take a truly preventive maintenance approach.
  • Self-directed: By focusing on optimization and automation, onPoint provides energy savings with minimal human intervention.

onPoint transforms big data into a tool for change and opens up the path to better performance, lower costs, and greater efficiency.

Buildings IOT’s innovative building analytics software transforms the way your building performs. Contact our team of experts to learn more about what we can do for you.