Watson Analytics is an intuitive, cloud-based analytics tool that will help TRIRIGA users explore their data for insights and display findings as dashboards and infographics for easy sharing. All without having to become a data scientist.
Watson Analytics guides data discovery and predictive analytics by using automatic visualizations and enables dashboard creation so that you can get insights and make informed decisions. Pairing Watson Analytics with data from TRIRIGA enables you to explore your integrated workplace management processes and obtain new insights on your day to day operations. The IBM Watson Analytics service will allow you to discover patterns and meanings in your data.
The TRIRIGA Connector for Watson Analytics gives you the ability to export your TRIRIGA data into Watson Analytics. With Watson Analytics, you can tune data, discover insights to help solve your business problems, and display your findings…
[Admin: To see other related posts, use the Watson tag or Analytics tag.]
Improving maintenance procedures through predictive analytics has recently seen many notable developments. Siemens is integrating IBM Watson Analytics into its MindSphere platform to help implement predictive maintenance schemes. Rockwell Automation recently launched its predictive analytics capability for factories and machinery. And PTC and Deloitte Digital announced that they are jointly developing predictive maintenance solutions for factory operations.
These developments are hardly surprising. Predictive analytics enables users to detect if, and when, machinery is likely to breakdown. For example, predictive analytics enabled Duke Energy to identify a slight increase in the turbine vibration of a steam turbine – after maintenance was performed. The subsequent repairs resulted in $4.1 million of potential power generation loss being prevented. Facility managers at plants and factories are therefore likely to be looking for such solutions to keep things running.
But is predictive analytics a natural sell in the world of commercial real estate? There is certainly some evidence of this. Since 2009, UK-based retailer Sainsbury’s has used software provider Verisae’s (now part of Accruent) predictive maintenance solution to reduce product loss from refrigeration failures. Since 2016, engineering firm KONE has partnered with IBM Watson to embed intelligent analytics in its elevators and escalators to improve their performance and reduce instances of unplanned maintenance.
Nevertheless, such examples are not necessarily the norm. According to our 2016 Global Energy Leaders Survey, 46% of the 250 facility managers surveyed said improving the collection, analysis and reporting of energy data from their electrical assets is a very important priority. In contrast, more granular asset-level energy management was only considered very important by 22%. And in our 2015 Green Quadrant for Building Energy Management Software, only 18% of the customer panel we interviewed considered maintenance scheduling and predictive maintenance to be a very important asset management functionality.
The average facility manager is therefore more likely to be concerned with basic data capture than advanced solutions like predictive analytics…
[Admin: This post is related to the 07.13.17 post and 03.16.17 post about IBM Watson Analytics, and the 08.01.16 post about the competitors of IBM TRIRIGA. To see other related posts, use the Verdantix tag.]
In my current project, there was a suggestion to extract (updated) data from TRIRIGA, with a high frequency, and import it into some kind of data warehouse (DW) or business intelligence (BI) solution. Then, from there, perform more advanced reporting and analytics. Have other TRIRIGA solutions implemented something similar? Are there any TRIRIGA best practices or recommendations for staging area, extract-transform-load (ETL), DW, or BI reporting solutions?
[Admin: This post is related to the 12.15.16 post about the IBM TRIRIGA Connector for Watson Analytics. To see other related posts, use the ETL tag or Analytics tag.]
The past few years have seen a surge of products and options that facility managers can use to examine, analyze, predict, and improve building performance and reduce energy costs. But connecting the dots in an increasingly complex web — the Building Internet of Things — often takes serious consideration, practical attention to budgets, and resolute effort.
Many organizations currently collect data, but want to use that data more effectively. This is the case for Texas Christian University. The university does a lot of data collection and monitoring but not a lot of data analytics, reports Chris Honkomp, assistant vice chancellor for facilities. “We have that on our list of issues to address in the next year, but are focused on installation of a new maintenance management system right now, and will address analytics as a part of this process.”
Many organizations have been collecting data for years, but as prices on the software that aggregates and trends these information points comes down, more facility managers are buying into data analytics of one sort or another. Just how far any specific organization has gone depends on a range of factors, including expertise, staffing levels, available data, time, and of course budget. A look at three facility organizations shows the range of current practices and challenges…
[Admin: To see other related posts, use the Smart Buildings tag.]
British designer and manufacturer of intelligent lighting and building control solutions, PhotonStar LED Group, announced on Monday that it was participating in the IBM InterConnect 2017 Cloud & Mobile Conference, between 19 and 23 March in Las Vegas. The AIM-traded firm also announced the commercial availability of the halcyon cloudBMS product from 1 April.
At IBM Interconnect 2017, the company said it would be presenting a talk outlining the key features of cloudBMS, a new cloud based solution that it said delivered an Internet of Things-based “building management system as a service” (BMSaaS). It said the new solution was built on the second generation of its low-cost retrofittable wireless monitoring and control platform, halcyonPRO2.
The new halcyonPRO2 added regulation of heating and cooling, shading and power management to the lighting control and environmental sensor network already in use in the first halcyon product. The cloudBMS, halcyonPRO2 and cloud-based analytics were combined to deliver a capable, scalable and secure “building management system as a service” (BMSaaS) solution, PhotonStar’s board explained, at a price point that would enable owners of small-to-medium-sized businesses to reduce energy and operating costs and realise new insights into their operations.
One of the key features of cloudBMS was the sharing of device data with asset management software packages such as IBM asset management packages TRIRIGA and Maximo, it added…
[Admin: This post is related to the 06.08.16 post about PhotonStar and machine-to-machine (M2M) technology, also known as the Internet of Things (IoT).]
Is there any way to embed the HTML code used for Google Analytics (or similar technologies) within the TRIRIGA code?
[Admin: This post is related to the 06.05.16 post by Dennis Salguero about Watson Analytics and Cognitive IoT.]
In November, we announced the launch of our TRIRIGA Connector for Watson Analytics – letting business professionals and facility managers easily integrate their TRIRIGA buildings data directly into Watson Analytics…
Self-service analytics: The answer to the data skills-gap
Today, getting access to the information you need to run your business probably means working across a number of different roles and teams: IT to get you access to your data, business analysts to help make sense of your data, and data scientists to help build predictive models. But the time and cost associated with getting the insights you need to solve daily problems can be prohibitive…
This is where Watson Analytics comes in. The easy-to-use interface is designed with business users in mind, enabling guided data discovery, predictive analytics and automatic visualization. For real estate and facility managers, Watson Analytics with TRIRIGA is your data scientist in a box…
How will you use your new insights?
The cognitive power of Watson Analytics allows it to uncover important and unexpected insights hidden in your data. You may uncover energy usage trends that you didn’t know were impacting your bottom line, or use Watson Analytics to reduce under utilized space and help lower your cost per square foot.
By exploring lease data, you might predict future capacity and achieve standards compliance. Or you may drill into your maintenance data for insights that will reduce operations costs and simplify service delivery…
[Admin: This post is related to the 11.15.16 post about the IBM TRIRIGA Connector for Watson Analytics overview.]