Making Sense Of Our Data With Microsoft’s Power BI
WHERE’D ALL OF THIS DATA COME FROM AND WHAT DO WE DO WITH IT?
Integrations with Microsoft’s Power BI
Data extraction and reporting tools are nothing new to folks in the BIM | CIM world; however, products and integrations that are able to ingest our Data continue to morph, providing much more visually appealing options to us. Microsoft’s Power BI is a perfect example as one of the (relatively) more recent options that the BIM | CIM communities are flocking to. Additionally, many vendors (both small and large) supporting the AEC Industry, are developing connected solutions directly integrated with design authoring tools that allow for seamless data migrations with minimal to no data loss into Microsoft’s Power BI.
On the surface, some of the immediate benefits to leveraging Microsoft’s Power BI include:
- Frees up valuable time for production staff. Whether you’re a technician, designer, modeler, engineer, architect, or other, introducing ways to extract data seamlessly from our BIM | CIM designs allows production staff to put more focus and effort on actual design and modeling processes.
- Share visual reports and dashboards securely. Engineers/Architects and all project stakeholders are able to review, interrogate, and analyze design Data without having to install a design authoring tool that they are likely not as familiar with.
- Collaboration with comment and issue tracking. Project design teams and additional stakeholders are able to provide feedback based on the reported Data being surfaced in dashboards, resulting in increased efficiencies and reaction times to achieve conflict resolution.
- View up-to-date Data with ease. Whether dynamic connections are established, or a re-extraction of Data is required to replace existing reports that the Power BI dashboards are reading, viewing up-to-date Data within this environment is a painless process.
Beyond these immediate benefits, Microsoft’s Power BI allows for multiple interactive and customizable viewing capabilities and connections to be hosted in one, or multiple, dashboard(s). Programmable and Automated solutions are enabling BIM | CIM designs to be viewed, interrogated, and manipulated in a user-friendly collaborative environment, where we can connect additional sources of Data to continue building into our model and Data federation, putting us on a trajectory where many are starting to view Microsoft’s Power BI as a potential Digital Twin solution.
Data – What is it Good For? Absolutely Everything
Asset Data
Thinking about the dashboarding concept from a high-level, what other types of Data can we report related to our BIM | CIM designs? Are we only limited to the Data directly associated with our modeled geometry within our BIM | CIM designs?
Not exactly. Data itself has also taken on a new life, as there are now many different interpretations as to what Data means depending on what it will be purposed for. When it comes to BIM | CIM designs, we have the In-Production aspect of Data where we can leverage it for labeling, tabling, and reporting purposes. Then comes the Review aspect, where we can leverage tools to extract Data from our BIM | CIM designs into more of a report format. Once Data has been extracted, we can look at additional ways we can leverage this data and integrate with solutions like Microsoft’s Power BI.
From there, we have many common applications and use cases where Data associated with our BIM | CIM designs are already being leveraged, which could include things like Quantification, Cost Estimation, Design Review, Model Validation, etc. Most of these applications of Data are fairly straight forward, as our design authoring tools are equipped to provide these capabilities with relative ease. Outside of the design environment, Data associated with our BIM | CIM designs are further being leveraged for Construction, Asset Management and Facility Management purposes, with majority of instances easily integrated with Microsoft’s Power BI.
Model Performance Data
Another aspect of Data that’s been gaining a lot of attention lately is associated with model performance. Model performance Data has the potential to include anything from analyzing project file sizes, to counting the number of modeled components in a particular file, to evaluating how many purgeable elements exist in your files, to missing reference links, to exploded geometry…and well beyond. Although this type of analysis of curated Data associated with our models and files may be a bit re-active in nature, it can help us truly understand our current state and provide insight as to how production staff are developing models.
Model performance is a critical component that can have many implications on a project’s delivery, as it can strongly affect production efforts, budgeting, scheduling, and more. Leveraging model performance Data allows us to properly mitigate design file complications to maintain high levels of modeling efficiency for production staff, with the added benefits of avoiding potential corruption of files and Data, and reduction in rework, later on down the road. Understanding that this concept isn’t as straight forward and requires a bit of innovative thinking and programming to acquire this type of Data, we could be seeing a monumental shift in how we are approaching designs and managing our models in general.
Individual Performance Data
A newer aspect of Data that has been gaining a lot of attention lately is specific to how production staff members perform on a project design. This type of Data collection and analysis is constantly monitoring individuals’ design and modeling habits and will even go as far as to provide upskilling or workflow recommendations to improve design and modeling habits. In order to be confident in the recommendations being provided, the Artificial Intelligence side of this will need to compare an individual’s modeling habits and commands being performed against a rather large sample set.
Taking the Artificial Intelligence side of this Data collection and mining a bit further, we move into the exploration of leveraging this Data for Predictive Design, Analysis and Performance. With confidence levels increasing in Data collected as we increase the size of our Data Lakes, we can deploy mechanisms that will provide recommendations as production staff are invoking specific commands or workflows, which essentially moves us from a reactive approach to a proactive approach. This predictive and proactive approach will provide that just-in-time training to design and production staff, which will most certainly affect model performance as well.
In Summary
Regardless of the Data being mined, Microsoft’s Power BI has certainly found a home across AEC. In turn, new careers, trades and specialties are being introduced as well with a focus of understanding, processing, surfacing and managing Data being mined.
From the outside looking in, it appears as though we’re on a trajectory where Data and Artificial Intelligence has the potential to replace the need for us to think throughout the progression of our BIM | CIM designs, maybe to the point where Automation will then take over and generate our designs for us. Yes, this may be a bit extreme to think, but is it?
Does this mean that production staff will need to consider a new career path to become a Data Analyst or Scientist? Not at all. Although there’s no harm in becoming more familiar with and educating ourselves with Microsoft’s Power BI and other dashboarding tools to understand how Data is being ingested and analyzed, there will continue to be a reliance for new Data to be collected to continue improving production and everyday workflows. And with all major design and collaboration platforms continuing to introduce new tools, workflows, integrations and overall product enhancements, the Data being mined will continue to evolve as new metrics are introduced.
