How Data Determines the Value of Your IoT ApplicationNovember 25, 2019 - 8 minutes read
The Internet of Things (IoT) offers a variety of benefits that organizations around the world are eager to leverage. But many of them aren’t deriving as much value from their IoT endeavors as they could.
Data is the lifeblood of IoT development. To extract the optimal amount of value from your IoT initiatives, you must learn how to properly manage your data. In this post, we’ll explore how automation can help businesses do this, how different IoT data sources impact your results, and how you can save on storage costs. Let’s begin!
The Need to Align Your Strategy With Your Data
In 2017, Gartner predicted that 20 billion IoT devices would be connected and online by 2020. Today, IoT’s adoption rate has already surpassed the research firm’s expectations, and it shows no signs of slowing down. Because of technological advancements, sensors can now be produced that are cheaper, smaller, and more effective than ever before. This has opened up the opportunity for nearly all organizations to dive into IoT.
As a result, the focus has shifted: Getting ahead in IoT no longer comes down to purchasing better technology and equipment. Instead, it all depends on how you use the data you collect. Of course, success isn’t the same for every business. Each company has different goals, so it’s imperative that their IoT solutions are tailored accordingly.
To make matters more complex, extracting actionable insights from data and making them accessible is already difficult enough for the average business. Some organizations attempt to solve this by adding more information and sources into the mix, but this often backfires and convolutes the situation.
In order to get the most out of your IoT investment, you must align your endeavors and data with your strategy. And that begins with understanding the roles of automation, your data sources, and storage.
Have Absurd Amounts of Data? Try Automation.
IoT devices produce a tremendous amount of data. Automation is the only viable way to manage this massive mountain of information.
Digesting, analyzing, and delivering data manually could never compete with automation’s real-time capabilities. By eliminating time-intensive, laborious tasks like hand-coding and data infrastructure management, automation drastically reduces the time and cost needed to act on insights while improving their quality and reliability. Besides this, team members now have much more time to focus on other important factors, like strategy.
When automating your data processing, consider doing so on a streaming basis from your field devices as soon as the data is created. Streamlining and expediting this processing flow closes the gap between data and insights even more.
Let’s look at an example to highlight the difference between processing your data in real time compared to later. Pretend you own a bus company with a fleet of hundreds of buses, and you want to understand and improve their performance. If you’re only downloading and analyzing your data at specific time intervals (e.g., the end of the day), then you’ll only find out a bus has broken down or been behind schedule much later after the fact. This affords you no time to address the problem in a timely manner.
On the other hand, if you’re analyzing your IoT-captured data in real time, you can diagnose and detect problems immediately when they happen. You can even get ahead of them since your sensors will be monitoring wear and tear. This type of preventative maintenance goes a long way towards maximizing the value of your operations.
Understand Your Different Data Sources
From bus brake sensors to airplane engine monitoring tools to video surveillance cameras, there are countless types of data sources and formats in IoT. While some of it comes in the form of structured information, semi-structured and unstructured data are becoming more commonplace.
Like our example above, it’s almost always better to filter these streams of data during ingestion as opposed to later on. To do this, you’ll obviously need to rely on automation; collating and processing this huge amount of data manually is too time-consuming. But to really simplify all of this, you’ll need to understand your IoT initiative’s information flow.
Comprehending how data flows through your process, from sensor to insight, allows you to see how well your IoT project aligns with your desired results. By understanding the smallest nuances of this flow, you can gain a holistic view of the critical, time-sensitive data most valuable to your endeavor.
You’ll also gain insight into what historical information should be stored for future reference. Doing this can help reveal trends over time.
How Do You Store Your Data?
All too often, organizations rely on increasing their data storage to support their IoT initiatives. Considering that IoT’s data growth is exponential, this is a shortsighted strategy that will only end up costing you more in the long run. Filtering and digesting your data in real time has been a big focal point of this post, and for good reason: By doing this, you can save data summaries instead of large transactional tables or raw information.
This pays in spades in terms of storage. Not only do you save on costs, but this also improves the speed, quality, and reliability of future processes. Sifting through what data is valuable and what isn’t is always easier when it’s fresh.
This isn’t to say there’s no value in storing raw data in some cases. Sometimes, it’s an absolute necessity. For these situations, cloud storage is often the most cost-effective short-term solution.
Data Is Your Most Precious IoT Asset
As sensors and devices become more affordable, IoT will only continue to explode in popularity. With the market expected to reach a value of $11.1 trillion by 2025, it has become clear that IoT technology is no longer only for big enterprises with big budgets or San Francisco developers working at a leading tech company.
Every organization can now use IoT to improve their operations. With the playing field becoming equalized, companies eager to differentiate themselves from the pack must examine how they process their IoT data sources. Data is your most precious asset in attaining an edge over your competition. And how far you get ahead depends on how you leverage your information.
Is your organization investing in IoT? What are your goals? And how does your data processing flow help you reach them? Let us know in the comments!Tags: app developers san francisco, data analytics in IoT, IIoT, internet of things, internet of things app, internet of things app developer, internet of things app developers, internet of things developer, iot, IoT app developer, IoT app developer San Francisco, iot app developers, iot app development, IoT app development San Francisco, mobile app developer San Francisco, mobile app development San Francisco