Recent research has revealed that in the last two years alone, 90% of all data has been produced globally, highlighting the dramatic growth of data production. This staggering statistic serves to demonstrate the sheer volume of information that is being created. As data is now an essential part of almost every technology which businesses utilize in order to function, it is essential that companies are proactive in managing their data usage.
The integration of Artificial Intelligence (AI), the Internet of Things (IoT), and robotics into business operations is heavily reliant on data. When appropriately linked with these technologies, data can enable organizations to gain a deeper understanding of their customers, products, services, efficiency, decision-making and financial performance. As such, businesses that do not take advantage of the data available to them risk being left behind by their competitors.
Gaining a comprehensive understanding of data and its capabilities is essential for businesses to capitalize on its potential. To ensure success, companies need to be aware of the corresponding software and hardware, as well as how to pinpoint the relevant data points for valuable insights and decisions. This article will provide an in-depth analysis of three data-centric technologies and how they can be utilized to improve the company’s profit margin.
The potential of Artificial Intelligence (AI) to assist organizations in areas such as inventory and Human Resources (HR) is immense when the technology is employed effectively. AI algorithms are utilized to uncover useful insights and patterns from large datasets. Furthermore, due to its capacity for learning, AI can be deployed to detect pre-existing behavior models or create new ones.
The integration of Artificial Intelligence (AI) and large datasets can be used to gain insights into consumer buying behaviour. By analysing data points such as prior purchases, online activities and interactions with brands, customer profiles can be created. This data can also be used to assess the likelihood of an existing customer base defecting, which could be beneficial in planning future marketing strategies.
By utilizing a similar method, it is possible to predict how other companies would act, thereby enabling one to adjust their own strategy accordingly. For example, one may discover that a rival firm has chosen to close 20% of its physical stores. By inquiring “why”, one may gain valuable insight into various market aspects which were previously unknown, and this information could be critical when deciding on the subsequent steps to take.
Remote management is a crucial element of many Internet of Things (IoT) devices and enables operation from a distance by humans or other machines. To further enhance corporate operations, these devices are also able to relay data back to their source for analysis. For example, IoT devices can be installed in shipping containers to monitor stock levels. By using analytics software, any shortages or excesses of a given material can be quickly identified and the exact cause of any disruption located. By closely monitoring operations, regular production of goods and stable monthly expenditure can be maintained.
Data collected by Internet of Things (IoT) monitoring devices installed on machinery can inform business owners of the need for servicing. These tasks can be planned in advance to improve cash flow and free up resources for other important tasks. For example, a business may choose to replace a large piece of equipment annually and use IoT data to decide when this replacement should take place.
Robots are commonly perceived as machines that perform repetitive tasks in factories and other production settings. Drones, a form of robot, are able to collect data and process it on-site or transmit it to a data centre. Additionally, robots equipped with robotic process automation (RPA) capabilities can automate mundane tasks that require interaction with various hardware and software applications.
Robotic Process Automation (RPA) has the potential to increase efficiency and reduce costs by automating mundane tasks and analysing large quantities of data. This method can lead to improved customer satisfaction, a decrease in data processing errors and a range of other beneficial effects.
A video by technology guru Bernard Marr explains RPA and how it may help with repetitive tasks is provided below.
The Importance of Modern Computing Methods
The availability of big data is made possible through the use of various technologies. These technologies provide efficient methods for storing, managing and utilising all available data, making them invaluable tools. Examples of such technologies include:
Hosted servicesThis technology allows businesses to store data and conduct analyses in a more efficient and cost-effective way, as it offers scalable resources and reduces the overall cost of data storage, thus freeing up IT resources for other purposes.
Local Processing at the PeripheryThis approach operates in reverse, carrying out the necessary processing operations close to the original source of the data. An example of this is utility grid equipment data, which can be managed at the edge of the network, thus freeing up resources for the key data that needs to be processed centrally.
5G,The rollout of 5G cellular network technology is in its early stages. Once complete deployment is achieved, it will enable enhanced connectedness and increased productivity through increased automation.
Ensuring the capture of high-quality data and having a well-structured system for assessing it are essential for taking advantage of these tools in combination with technologies such as AI, the Internet of Things, and robots. With these two elements in place, businesses have unlimited potential to maximise the worth of large volumes of data.