Viewpoint: can acquisition systems keep pace with the Age of Data?

We are in the Age of Data. The amount collected in the last two years accounts for 90% of all data ever recorded. This has a profound effect on industries as companies rely more on this information to make business decisions.

Engineers require dependable, precise and user-friendly data acquisition systems. However, innovation in the data acquisition market has not kept pace and the tools must evolve faster for those who need data to enlighten their design decisions.

Readily available tools are lacking in two ways: providing simple yet flexible software and making measurement system setups more accessible.

Innovation in the data acquisition market has not kept pace and the tools must evolve faster for those who need data to enlighten their design decisions

Users must select between limited configuration software, which assists with basic data recording but can’t be modified to meet application requirements, and custom data acquisition applications programmed from scratch.

Hardware vendors provide software with the essentials for recording data from devices, but push users to a different programming tool when they face challenges beyond the original software’s capabilities.

Software should evolve to span configuration and customisation. In a survey of 3,800 engineers, 27% said developing software for their application was the most time consuming part of their task, while 21% spent most of their time struggling with system setup.

One extreme to another

Engineers use two types of data acquisition software at opposite ends of the spectrum.

Fixed-functionality software is good for setting up a quick, simple measurement to configure basic settings like sampling rate. But custom software applications give users the power to program any functionality if they have the know-how and patience.

Users who want a typical data acquisition application for acquiring and saving data, with minor modifications like basic conditional logic, must choose between these two extremes.

When their needs extend beyond the software that ships with their hardware, they must opt for a custom, programmed solution.

There’s no reason data acquisition software can’t evolve to better fill this gap. A solution would involve offering a continuum from configurable measurements to customisation through programming. This would increase efficiencies and remove the present trade-off.

Engineers can choose from a variety of systems featuring flexible, modular data acquisition hardware that they can adapt and reconfigure to meet changing I/O and sampling needs

When building a measurement system, setup is time-consuming, and done incorrectly can introduce errors that may be hard to debug.

Engineers can choose from a variety of systems featuring flexible, modular data acquisition hardware that they can adapt and reconfigure to meet changing I/O and sampling needs. This is highly beneficial to users who face evolving system requirements, but the flexibility complicates setup.

Consider a single-function device like a handheld instrument for measuring temperature. When using this, the risk for error in setup is low.

Conversely, a modular data acquisition system features a range of I/O options and provides many different measurement combinations. This helps lower total system cost, since the same set of hardware can be adapted to serve a range of applications. But with that comes more configuration options that can complicate setup.

Driving innovation

Software packaged with data acquisition devices does little to help users understand and document system connections such as wires between sensors.

Better data acquisition software could reduce system setup complexity through improved system visualisation, recommendations for correct wiring, and better checks for channel configuration.

Data acquisition plays a critical role in driving innovation. Engineers rely on acquiring the right data to support design decisions; advances in software could have a tremendous impact on improving their efficiency.

To achieve this, software must evolve to fill the gap between limited configurable software and flexible but costly custom programmatic solutions without increasing setup complexity.

It’s time to demand more from the software we use to acquire data.

• Michael Neal is software product manager at National Instruments Corporation (NIC)