Real-Time Data Management Is Helping These Industries Evolve

There’s a huge difference between data and real-time data, with the latter having infinitely more potential. What’s more, while “real-time” is a buzzword that a lot of big data proponents like to throw around these days, it is an excellent way to describe the flow of today’s biggest digital solutions. It denotes that the information, or digital content, is always flowing, always updating, and instantly available. More importantly, it’s often processed through machine learning to tell us more about what’s happening through earned insights.

Of course, that data stream doesn’t do anyone good without the appropriate real-time data management solutions in place. It’s not just about the data flowing continuously, or who’s using it, but also how it’s being categorized and stored. With such a massive store of information, there has to be some governance in place to preserve, organize, and utilize it all, even if it’s being accessed at a later date.

The information can drive business decisions if it’s interpreted correctly and insights are extracted. But generally, most data streams cannot be used in their raw form, and that’s precisely where real-time data management comes into play. Here’s a look at how real-time data and real-time data management are transforming modern industries.

1. Healthcare

Whether you’re talking about cutting-edge medical research or tried-and-true personal care at a local physician, the healthcare industry has always been incredibly data-driven. Doctors and healthcare professionals are constantly using gathered information – about medical histories, genetics, body readings, and more – to make proper diagnoses or check their patients’ health. Researchers, on the other hand, are using years of harvested information to discover new treatments and medicines.

For so long, most of this data has been static, relegated to a folder, jotted down on paper, or manually entered into a digital system. However, today’s real-time data is changing the game. For instance, real-time body statistics and information, collected through smartwatches and a user’s smartphone, are providing doctors with a much deeper understanding of their patients’ health and lifestyles. This allows them to make more accurate recommendations and monitor their patient, providing guidance along the way, well before something goes awry. Additionally, it also enables precision medicine, where health problems are being preempted through real-time information and real-time data management.

2. Construction

The construction industry has always been a very in-the-moment landscape where things are planned out extensively. However, when faced with challenges, decisions are generally revised on-the-fly. Real-time data management can reshape operations by not only providing highly valuable insights, but also helping to discover new methods, processes, and solutions, many of which are a direct response to encountered complications.

The evolution of equipment maintenance is a great example. Typically, it’s reactive, and while certain tasks are done to prevent the system or hardware from breaking down – like topping off fluids, changing filters, and storing the equipment appropriately – most teams take action after an event has happened or after a piece of equipment has broken down.

Real-time data and predictive analytics can vastly improve this practice by enabling more proactive maintenance. A vast trove of information about a piece of equipment can be collected and analyzed to identify declining performance, potential failures or breakdowns, or new methods of maintenance.

Perhaps a machine is not getting the proper amount of grease or lubrication and it’s affecting performance. Or maybe it’s causing premature wear on the system that will eventually lead to a breakdown. Real-time data can fine-tune that process through information such as when the lubricant was applied, at what temperature or conditions, and how it affected the performance of the machine. The data can also be used to predict or plan for future events, like hardware shutdowns, which would cause massive delays for a project.

3. Agriculture

Traditionally, farming and agriculture are not industries you might associate with big data, cloud computing, or artificial intelligence. However, things have changed and data analytics, along with reliable real-time data management, are absolutely essential for agriculture operations to thrive. Predicting or reacting appropriately to the weather as well as local conditions, assessing the land, and adjusting to market changes are all operations that can be driven and enhanced by real-time data.

Referred to as smart farming, the strategy leverages the Internet of Things, cloud computing, and real-time data analytics to better understand and control the entire supply chain, from the growth of food to a sale right off store shelves. The incoming data is fed into an analytics platform, with access to machine learning, which extracts usable insights thanks to access to both real-time and historical information.

4. Banking and Finance

As modern currency goes digital, it will become increasingly important for the banking and finance world to keep up, which means utilizing extensive data stores to understand the markets. Knowing how customers are using their accounts, which investments or trades are worthwhile, and even how to deal with potential security challenges will all come from real-time data streams and proper analytics.

Data may also shape how consumers and businesses are using their money. On the opposite side of the equation, people also have access to similar tools for tracking expenses, bills, and leisure spending, allowing them to adjust accordingly, especially now with prices climbing steadily. These tools, which also use real-time data, can help people make important decisions with unprecedented accuracy. They learn where to invest their money, how much and when to save, where to cut expenses, and how to better manage their finances overall.

5. Retail and e-Commerce

From physical goods through retailers like Amazon to digital goods through places like Netflix, real-time data management continues to transform the market. These brands are using real-time data to understand their customers’ needs, sentiments, and behaviors, in order to provide top-notch recommendations and personalized service.

But the technology is making waves across the entire field, and not just during dealings with customers or clientele. Amazon uses real-time data to identify and deal with potential fraud, for example. Aurora, the company’s buyer fraud service, was able to gain scalability for better support while costs were cut in half – something that wouldn’t be possible without the proper data management solutions.

Other companies might use real-time data management to address sudden market changes like shortages and price fluctuations. Real-time data plays a crucial role in thriving operations today and will only become more integral in the future.

The Modern World Runs on Data

Nearly all industries – even those you don’t see listed here – now run thanks to some form of real-time data or analytics. But all of that information, whether it’s flowing in or out, needs to be processed and utilized correctly before it can have any value, which is at the heart of real-time data management. Data veracity is crucial as well, which means considering its accuracy, source, and algorithmic value.

When appropriately leveraged, real-time data and extracted insights can drive both business and operations, helping to vastly transform efficiency, productivity, and output. The industries here are wonderful examples of that evolution in action.

The post Real-Time Data Management Is Helping These Industries Evolve appeared first on IoT Times.

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