It is said that the amount of data created around the world is growing at such a rapid rate that 90% of it was generated in the last two years alone.
It is said that the amount of data created around the world is growing at such a rapid rate that 90% of it was generated in the last 2 years alone. This surprising statistic reveals the extent of data generation. This tremendous increase in the amount of data requires companies that use it to be increasingly intentional about how they use it, especially as it becomes fundamental to virtually every system a company uses to support its operations every day. .
Data is essential for other technologies, including artificial intelligence (AI), the Internet of Things (IoT) and robotics. When intelligently integrated with these technologies, data can help companies better understand customers, improve products and services, become more efficient, make better decisions and generate more revenue. It is becoming so important that companies that fail to make effective use of data are likely to fall behind their competition.
But knowing how to make the best use of data requires understanding how it works in other technologies and tools. This knowledge is especially true for companies that rely on many data sources and must determine how to find the pieces that will lead to truly insightful and actionable results. In the sections below, we take a closer look at three technologies that interact closely with data and how they can be leveraged for greater business success.
AI
When used strategically, AI has vast potential to help companies in areas ranging from inventory to HR. AI algorithms are used to examine data and find relevant information and patterns in a way that humans never could. And as AI has the potential for learning, it can identify already established behavior models or create new ones on its own.
For example, AI and big data can be used together to discover consumers' purchasing habits. Information such as past purchases from your company and others, online behavior and interaction with brands can be gathered to form a picture of each potential buyer. These profiles can also be used to determine things like the established likelihood of customer defection. Such findings can be invaluable in creating new promotional initiatives.
You can use a similar process to determine competitors' likely behavior and develop business strategies accordingly. For example, you may discover that a competitor plans to close 20% of its physical stores. Asking why and uncovering market forces you were previously unaware of can be invaluable in determining your next move.
IoT
One of the goals of IoT devices is the ability for humans or other machines to control them remotely. Another is that these devices send data back to these sources for analysis, which results in insights that can improve business functioning. For example, IoT devices can be placed in containers to track inventory. Analysis programs can see where delays are in terms of excess or shortage of a certain material. Maintaining the right balance can ensure a consistent flow of products manufactured and a predictable budget from month to month.
Data from IoT monitoring devices connected to equipment can inform company operators when it is time for maintenance, repair or replacement. And these activities can even be scheduled, to create a more stable cash flow and free up money for other critical initiatives. For example, a company can set a schedule for replacing a major machine per year and use IoT data to determine the order in which replacements should occur.
Robotics
The common image of a robot is that of a machine that performs repetitive tasks, such as on a manufacturing assembly line. However, robots can take other forms, such as drones, which collect data and process it, or send it to a central processing center. Another type of robot is one that performs robotic process automation (RPA), which carries out processes that interact with other digital systems and software.
RPA can be used to perform repetitive tasks or examine large volumes of data and detect which parts might be useful for analysis. This process can be implemented in numerous applications. By implementing such actions, business operators can significantly reduce data processing errors and increase efficiency, resulting in both reduced costs and other positive outcomes, such as increased customer satisfaction.
The following video from technology expert Bernard Marr provides more information about RPA, highlighting its repetitive processing function.
The role of computing technologies
A series of technologies that support big data make all this activity possible. These tools allow you to store, manage and use all available data quickly and effectively. They include the following items:
- Cloud computing allows companies to store data and perform analysis in environments that can expand or contract capacity as needed, making data storage costs more predictable and reducing the need for network management and extra hardware that may only be used periodically. .
- Edge computing performs the opposite function, processing data closer to its source. For example, data collection from utility network equipment may be processed at the edge, leaving valuable bandwidth available only for highly relevant data that must be processed alongside other information collected in a central repository.
- 5G, the fifth generation of cellular network technology, is still in the early stages of deployment. When fully deployed, it will enable much greater use of IoT devices and therefore greater connectivity that will increase the efficiency that comes with more automation.
The keys to using these tools in combination with technologies like AI, IoT, and robotics are to ensure you collect quality data and have a carefully designed system to analyze it. With these two elements in place, companies can find countless ways to use large amounts of data to their best advantage.
