My first introduction to LabVIEW was from an early adopter of the graphical language in the condensed matter physics lab at the University of Pittsburgh. This person had taught himself LabVIEW, and insisted that those who worked for him gain first-hand experience in using a graphical language to increase productivity.

His approach was to have his employees work through the learning curve with little or no assistance.  I managed to improve my learning curve and could write multiple applications that functioned as required. I became quite comfortable and proficient with LabVIEW … or so I thought.

And then I started to work with Data Science Automation where I learned how LabVIEW really works. I was introduced to many best practices for developing applications using LabVIEW. For example, a simple idea such as Global Variables while fine in small application can quickly blow-up when used in large complex applications. National Instruments offers a large selection of courses that cover the basic introduction through large application development and management. While the NI course work may cover most of the critical ideas and concepts, it could be considered too general in nature and require a extra time and costs to pick-up a few key points.

Data Science Automation can create custom instructions tailored to the needs of the novice as well as the experienced developer. We can review existing code bases, provide customized training, and targeted feedback in areas where there are alternative approaches that will help improve the consistency and best practices.