Research conducted recently indicates that almost 90% of all data in the world has been generated in the past two years, underscoring the exponential growth of data production. This remarkable figure illustrates the sheer magnitude of information being generated, and as data has become indispensable to the functionality of almost every technology employed by companies, proactively handling data is now imperative.
Effective integration of Artificial Intelligence (AI), the Internet of Things (IoT), and robotics into business operations is highly dependent on data. When properly harnessed and used in conjunction with these technologies, data can provide organizations with invaluable insights into their customers, products, services, efficiency, decision-making, and financial performance. Consequently, companies that fail to capitalize on the wealth of data available to them run the risk of falling behind their rivals.
Acquiring a comprehensive grasp of data and its potential is indispensable for businesses looking to leverage its capabilities. In order to succeed, organizations must possess knowledge of the appropriate software and hardware, as well as be adept at pinpointing the relevant data points for valuable insights and decisions. This article offers a detailed examination of three data-centric technologies and how they can be employed to enhance a company’s profit margin.
AI
When utilized effectively, Artificial Intelligence (AI) has tremendous potential to aid organizations in areas such as inventory and Human Resources (HR). AI algorithms are utilized to uncover beneficial insights and patterns from vast datasets. Moreover, owing to its ability to learn, AI can be leveraged to detect existing behavior models, as well as develop new ones.
The convergence of Artificial Intelligence (AI) and vast datasets can be utilized to gain valuable insights into consumer buying behaviour. By closely analyzing data points such as prior purchases, online activities, and brand interactions, customer profiles can be constructed. This data can also be utilized to evaluate the probability of existing customers defecting, which could prove advantageous in devising future marketing strategies.
Through the utilization of a comparable approach, it becomes feasible to anticipate the actions of other companies, thereby allowing for strategic adjustments to be made. To illustrate, imagine one discovers that a rival firm has opted to shutter 20% of its brick-and-mortar locations. By probing to uncover the “why” behind this decision, one may gain invaluable insights into various market aspects which were previously unknown, and this information could prove pivotal in determining the next course of action to pursue.
IoT
Remote management is an essential component of numerous Internet of Things (IoT) devices, which enables their operation from a distance by either humans or other machines. These devices are also capable of transmitting data back to their source for analysis, thereby further enhancing corporate operations. For instance, IoT devices can be deployed in shipping containers to monitor inventory levels, and through the use of analytical software, any shortages or surpluses of a given material can be speedily identified, and the underlying cause of any disruption located. By closely monitoring operations, steady production of goods and stable monthly expenses can be maintained.
Data collected through Internet of Things (IoT) monitoring devices installed on machinery can provide business owners with insights into the need for servicing. These tasks can be scheduled in advance to optimize cash flow and allocate resources for other essential duties. For instance, a business may determine to substitute a major piece of equipment on an annual basis and rely on IoT data to determine the best time for this replacement to occur.
Robotics
Robots are often characterized as machines designed to carry out repetitive tasks in factories and other industrial settings. Drones, which are a kind of robot, can collect data and process it either on-site or transmit it to a central data center. Furthermore, 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) can boost efficiency and reduce expenses by automating mundane tasks and analyzing vast amounts of data. This approach can result in enhanced customer satisfaction, a reduction in data processing errors, and an array of other positive outcomes.
Below is a video by renowned technology expert Bernard Marr, which elaborates on RPA and its potential in automating repetitive tasks.
The Significance of Contemporary Computing Approaches
Various technologies facilitate the accessibility of big data. These technologies furnish effective ways of storing, managing, and utilizing all the available data, rendering them indispensable tools. Some examples of such technologies include:
Hosted services:
This technology enables businesses to store their data and conduct analyses in a more cost-effective and efficient manner, as it provides scalable resources and lowers the overall expense of data storage, thereby freeing up IT resources for other essential tasks.Local Processing at the Periphery:
This approach works in the opposite direction by conducting necessary processing operations in close proximity to the original data source. For instance, utility grid equipment data can be managed at the network’s edge, liberating resources for the central processing of the key data.5G:
The deployment of 5G cellular network technology is still in its nascent stage. However, once fully rolled-out, it will enable greater connectivity and heightened productivity through increased automation.
Capturing high-quality data and establishing a well-structured system for evaluating it are crucial for leveraging these tools in combination with technologies such as AI, the Internet of Things, and robots. With these two factors in place, businesses possess limitless potential to maximize the value of large amounts of data.
