The Top Challenges of Visualizing Time-Based Measurement Data

Contributed by Derrick Snyder | Austin, TX

I’ll put this bluntly: in industry today, data is our single most valuable resource. The more we can understand data, the more potential we have to improve. Whether we’re driving process efficiency or reducing product cost, trending public opinion or observing environmental patterns, data enables us to make decisions that better our world.

In the not-so-distant past, the biggest challenge with data was simply obtaining it. Today, data is all around us; it’s in the air we breathe, the social networks we update, and the conversations we hold. Today’s challenge is no longer in obtaining data – it’s in effectively managing and visualizing data so that we can make sense of the all the data we’re able to obtain (and do so faster than our competitors).

In the next few blog posts in the coming weeks, I will be addressing the top data challenges faced by scientists and engineers who seek to acquire “data” that can be measured of some sort of phenomenon over time; for example, measuring temperature fluctuation in a temperature chamber for the duration of a given test, or monitoring the voltage being supplied by a battery. Collecting this type of data often presents a unique set of challenges when it comes to visualizing acquired data.

Stay tuned!

– Derrick Snyder

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About Derick Snyder

Derrick Snyder is a product manager for NI DIAdem measurement data processing and visualization software at National Instruments. He received a bachelor’s degree in Computer Engineering from Vanderbilt University.