From lifesaving medical devices to dependable EV batteries, test helps ensure that safe, reliable, and innovative products enter the market. This critical phase of product development generates valuable data and, in turn, actionable insights. In other words, we can use data to uncover trends, correct errors, improve performance, and more. Sounds simple enough, right?
Knowing how to harness data and respond to improvements in the data landscape, however, is a challenge that affects us all. Small test teams and large, established tech companies alike are struggling to take full advantage of data. Although we may be generating data that can help our products reach peak performance, it doesn’t matter if we can’t access it, study it, protect it, and communicate our findings properly.
When it comes to data management, security, and scalability, the challenges we face are real—but they’re not insurmountable. If we can identify and remove the obstacles that lead to data inefficiencies and gaps, we can find effective remedies, fully leverage test, focus on innovation, and stay ahead of the competition.
Data challenges have existed since the “information explosion,” but emerging technology is reigniting the need to remain competitive. In the past, as long as you were using data in any capacity, you were sure to grow. But it’s no longer enough to be efficient—to remain competitive, you must be willing to constantly innovate. After all, in an innovation-driven economy, the biggest value comes from optimizing your products and services, and we do so through data.
Today we have more data available to us than at any other point in history, and we need this data to make informed decisions. Engineers need it to safeguard products and ensure performance, and other parts of a business, like marketing and operations, need it to improve their strategies.
One challenge that some companies face involves having too much data. Say you have an unlimited amount of data at your fingertips. How can you tell what’s valuable and what isn’t?
An overabundance of a data isn’t a new problem, but more companies are revisiting how to take control of it in the wake of emerging ancillary technologies that weren’t previously available.
As cloud infrastructure, artificial intelligence, machine learning, and 5G evolve and converge, they afford solutions to a glut of data. For example, machine learning has the capacity to sort through massive amounts of data to identify trends, discover hidden patterns, predict potential situations, and adjust to them automatically. These insights subsequently inform decisions and can optimize the entire product development life cycle and positively impact companies’ bottom lines.
These same technologies are key to addressing three other major data challenges that impede innovation and competitiveness...
Security
In talking about the sanctity of data and the ways that it can positively impact key growth metrics, it’s imperative to consider the security behind keeping that data safe and out of a competitor’s grasp. When you choose a solution, there must be guarantees that your data is safe. One factor to consider is access control, which goes beyond just ensuring that individuals at your company have access to data—there must be peace of mind in knowing that individuals only have access to the data they need and not have access to data beyond the site and test station they work at.
Another security factor is storage location. Choosing between an on-premise solution versus a cloud solution like Microsoft Azure or Amazon Web Services is a decision that your IT and engineering teams must agree on. Investing in secure data solutions is one critical way to mitigate unnecessary risk and is an important data challenge to address.
Scalability
Data challenges are not unique to any one industry or company, regardless of size. In fact, the more you grow, the more challenging collecting and sorting through data becomes. One example of this is a company that uses 10 test systems that run 24x7, and for that number of systems, they need to take two days per week to extract, clean, and analyze the data, which then gets manually uploaded. When looking at their scalability, this manual methodology is simply unsustainable.
There are methods to scale efficiently to get the most out of your data that do not require sacrificing time and energy. For example, tasks like ingesting data, aggregating data, data engineering, processing, analytics, and reporting can be accomplished through automation, which saves teams thousands of hours and allows companies to take full advantage of data insights that might otherwise not be available or wouldn’t be available timely. Additionally, as companies reimagine what data can do for them and look to break down data silos, a number have found success through tools like SystemLink™ software, which has helped teams maintain a competitive advantage and save time. Regardless of the direction your team takes to grow and evolve, remaining competitive in this market demands innovation.
Openness
In talking about why it’s crucial to keep data safe and, to some companies, on-premises, it’s clear that companies value their independence. Reimagining your data solutions should not mean changing every aspect of your organization and the ways in which the people in it operate. That’s why it’s important to adopt solutions that work with the tools already in place and are easy to integrate into existing infrastructure. For example, here at NI, we take pride in providing open, interoperable solutions that are compatible with existing technologies and are IT friendly. Openness enables easy adoption of new technology by test groups that would be implementing it and IT teams who would support it.
Getting the most valuable and actionable insights from test data is important, and not just for your company’s bottom line—data ensures safety for users and drives optimal product performance that builds trust in your product and in your organization.
If you own an EV, having a guarantee that the battery won’t overheat and fail is critical. A medical device that you rely on to stay alive should be dependable 100 percent of the time. When you’re flying home on an airplane, you want peace of mind knowing that the manufacturing required to put that plane in the air underwent rigorous testing to ensure its safety in every situation. These assurances come from test data. Data helps teams improve performance, and if those products were to fail, data drives decisions that ensure they can fail safely.
Humanity once conquered fire, and that led to a revolutionary new way of living. Since then, we’ve mastered agricultural innovation and spurred the industrial revolution. Dominating the data revolution and capturing the full potential of data insights is the key to unlocking the next phase of human innovation.
Tackling these data challenges is no simple task, but we can work together and Engineer Ambitiously™ to find viable solutions that support everyone’s goals.
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