DAQifi’s New Wireless Data Acquisition Logger Empowering Big Data Trends


For the last 10 years, Colorado based company has been developing high-quality data acquisition systems that can be used in a number of locations and venues.  DAQ or data acquisition is a process for sampling and mapping signals that can quantity physical real world conditions into a set or series of values that can be gathered and measured by experimenters or data scientists.  Data loggers that use DAQ technology allow computers to convert analogy waveforms into complex digital values for processing.

Generally speaking DAQ systems function in a number of fundamental ways:

  1. Analog-to-digital systems that can convert sensor signals to CPU values.
  2. Sensor signals that can be converted into useable digital values.
  3. Physical parameters that can be quantified by electrical signals.

 DAQ systems rely on software protocols that are run using basic programs such as Basic, C++, Java, Fotran, LabView, Pascal and a host of other basic programs.  The term data loggers are usually reserved for stand alone systems that don’t integrate with other more complex systems.

While there are a host of open source softwares that allow users to use DAQ systems fairly comfortably the field has only recently opened up to private companies that have begun to build custom DAQ software.

The promise that DAQ systems bring to the modern economy is a powerful vehicle in which to allow data scientists to aggregate multiple streams of “big data”. Big Data is the structured exploration of hidden trends, patterns and variables within company or scientific data. It’s easier to think of it as patterns within an overly complex process that can’t be identified by humans.  Using regressive algorithms powered by increased processing power DAQ systems can help expedite the process.

DAQ-enhanced big data can benefit us in three major ways:

  • Allow innovation and improvement
  • Allow companies to find competitive advantages that weren’t precisely accesible
  • Identify inconsistencies and inefficiencies
  • Identify new cause and effect relationships

As discussed in a recent SAS article…

“The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term “big data,” businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends.

The new benefits that big data analytics brings to the table, however, are speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.”

As the global economy shifts towards more integrated networks having systems and methods like DAQ in place will allow companies to seamlessly transition into a big-data empowered global force.

big data and data loggers

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