If the term “data robot” brings to mind characters like R2D2, think again. Learn how the field of data robotics is transforming organizational efficiency and innovation.
When most people think of robots, their first thought goes to charming on-screen characters like WALL-E or R2D2. Others have a more cynical view of the man-made machines, picturing them as advanced AIs ready to take over the world and subjugate humankind.
The reality of robotics today, though, is much more nuanced. At its core, robotics is about artificial intelligence and data analytics, fields that have seen vast innovations and advancements in the past decade.
With more businesses adopting technological solutions to stay competitive in a quickly transforming market, it’s essential to understand the role of data robotics in bringing a company up to speed. Today, we’ll look into what makes a data robot and its potential to shape a business’s digital transformation efforts.
The rise of the data robot
As Artur Dubrawski, director of Auton Lab at Carnegie Mellon University, explains, “Robotics was always about data.” Data is at the core of what it means to create functional robotic technologies: to perform a function, a robot must be able to sense, plan, and, finally, act.
This takes a tremendous amount of data processing and analytical capabilities. As such, those working in the field of robotics have long known what it’s like to work with what we now call “Big Data” to create functioning artificial intelligence.
Now, as more and more businesses recognize the importance of having access to vast quantities of quality data, the role of robotics is becoming more apparent. As Dubrawski notes, “data analytics and robotics are very closely related and often overlap with one another.” And now, many organizations use robotics applications strictly for data analysis.
Different types of data robotics
Artificial intelligence—the ability to self-learn—is the foundation of all robotics applications. This AI can have a variety of use cases in businesses today but often fall into one or more of these categories:
1. Machine Learning
An emerging area of artificial intelligence/robotics, machine learning aims to enable an algorithm to be able to act without being explicitly programmed to take each specific step necessary for that action.
A good example is self-driving cars, which take in real-time data and learn as they drive. This, of course, is a highly specialized form of data robotics able to take in multiple streams of data and parse meaning from them. Some machine learning applications also enable natural language recognition and processing, allowing them to understand and communicate in human language.
2. Robotic process automation
One of the most common applications of data robotics in business today is robotic process automation. RPA commonly involves utilizing AI to automate tedious, often low-value tasks, like updating and organizing administrative information. By automating these repetitive tasks, teams can focus more time on higher-value work that contributes more ROI to an organization.
3. Intelligent process automation
RPA’s more advanced cousin, IPA, takes automation a step forward. Instead of simply being able to execute relatively easy, rules-based tasks, IPA can handle more complex business processes without the need for human intervention. Technologies like machine learning and natural language processing enable these tools to make more significant decisions based on statistical data, ultimately improving a company’s efficiency and ability to stay agile.
Benefits of data robotics
Today, companies handle more data than ever before, and it can be hard to keep up with the sheer volume of structured and unstructured data daily. By automating the organization and management of this data, your teams will save a ton of valuable time.
One of the great things about RPA is that it can work 24/7, 365. This allows your employees to spend their time on higher-value projects and tasks that can improve your company’s efficiency and bolster employee engagement.
A significant benefit of utilizing data robotics for analytics is error reduction. Even the most highly-trained analytics team is bound to make mistakes from time to time, and those mistakes can render data sets unusable. If you’re worried about securing high-quality data and analytics, a data robot can help.
Along with reducing errors, you’ll also receive better overall insights from your data when you allow robotics to help. No matter how big of a data set this technology is working with, it can quickly learn to see patterns and draw conclusions.
With the ability to consistently learn and improve based on the amount of data you give to train, data robots are highly flexible and scalable in the long term. And the larger your RPA or machine learning algorithms grow in capabilities, the easier it will be to get a great return on investment.
Is your business ready for a data robot?
Ultimately, the applications of data robotics in improving organizational processes are vast. Want to explore how data robot technology can help take your business to the next level? Reach out today to learn how you can take advantage of these tools.