Today’s post is part of a series exploring areas of focus and innovation for NI software.
Today’s Featured Author
Shelley Gretlein is a self-proclaimed software geek and robot aficionado. As NI’s director of software marketing, you can find Shelley championing LabVIEW from keynote stages to user forums to elevator conversations. You can follow her on Twitter at @LadyLabVIEW.
Data is critical to engineers and central to LabVIEW. Most engineering and scientific applications are primarily concerned with turning real-world signals into meaningful information for the purposes of measurement and control. As a result, data from hardware drives the behavior of these systems—making a language built around the data itself a natural expression of how these systems should behave.
Graphical data flow is the primary way to describe the behavior of a LabVIEW system. LabVIEW graphical diagrams literally depict the flow of information between functions, which execute when they receive all required inputs, and afterward produce output data that is then passed to the next node in the dataflow path. Visual Basic, ANSI C++, JAVA, and many other traditional programming languages follow a control flow model of program execution. In control flow, the sequential order of program elements determines the execution order of a program, as opposed to the data itself. In LabVIEW, the flow of data rather than the sequential order of commands determines the execution order of block diagram elements. Consequently, LabVIEW developers can create block diagrams that have simultaneous operations.
Dan Woods, Forbes contributor, presents a compelling case that our need and desire for data is only growing with the Internet of Things. Taking the reports by analysts, the billions of sensors and millions of connected devices will yield almost $2 trillion by 2020. However, says Woods, “..the path to creating that value is not what most people think it is. A problem that has not disappeared is what to do with all of the data generated by the sensors. The challenge is not just the volume of data, but the fact that the modern world of data analysis is something that uses an ensemble of technologies and each will require its own slice of the data.”
This type of insight is exactly why we on the software leadership team at NI have significantly increased our investment in data exploration, discovery, and engineering analytics in our platform. You can see results of this increased investment in several key areas including, but not limited to:
InsightCM Enterprise—a deployment-ready software solution with tightly integrated, flexible hardware options for online condition monitoring applications. The suite can acquire and analyze measurements, generate alarms, help maintenance specialists to visualize and manage data and results, and simplify remote management for large deployments of CompactRIO-based monitoring systems. It provides insight into the health of critical rotating machinery and auxiliary rotating equipment to optimize machine performance, maximize uptime, reduce maintenance costs, and increase safety.
DIAdem—a single software tool that you can use to quickly locate, load, visualize, analyze, and report measurement data collected during data acquisition and/or generated during simulations. It is designed to meet the demands of today’s testing environments, which require you to quickly access, process, and report on large volumes of scattered data in multiple custom formats to make informed decisions. DIAdem is a component of the NI Technical Data Management (TDM) solution.
DIAdem DataFinder - Locate data quickly and intuitively using the NI My DataFinder. Each version of DIAdem software includes a self-configuring data management system that provides advanced search and sophisticated data mining functionality right out of the box—you do not need any additional IT support to set up or maintain DIAdem.
Some of the data interactions you find in these other products make sense to bring into more NI software products, including LabVIEW—where data insights are going to be more valuable and more necessary. Stay tuned for even more approachable and interactive data analysis capabilities. In the meantime, share your engineering data needs with me here.
What do you need from your data? Let us know in the comments.