IoT Data Management: The Benefits, Challenges, and Strategies

Business leaders need an effective IoT data management strategy to optimize and store collected data as well as implement IoT to its maximum potential.

The advent of modern technologies such as IoT has helped businesses acquire large volumes of critical customer and operational data. Organizations utilize the acquired data for analysis, maintenance, and enhancing the efficiency of operations. This trend of aggressive data collection and utilization has led to the rise of data-driven business practices. However, storing and sharing the collected data can be a major concern for business leaders. With data privacy issues making headlines, businesses have to be extremely careful with critical data. To implement IoT solutions in a secure and effective manner, business leaders need to create an IoT data management strategy. An effective strategy can help reduce the impact of cybersecurity risks and ensure the privacy of data. Additionally, IoT data management strategies allow business leaders to reduce costs and implement IoT solutions efficiently. IoT data management helps organizations ensure that the challenges faced by IoT infrastructure do not outweigh its benefits.

1. Benefits of IoT Data Management

IoT data management can help businesses in the following manner:

Product Development

IoT data management can help businesses understand the usage patterns of customers. These usage patterns can be incorporated into the design and development stages. With this approach, businesses can identify errors in their current design and make changes accordingly. IoT can also allow businesses to carry out field tests for their products. In this scenario, IoT data management can help in identifying potential wear-and-tear areas and expected product lifetime. IoT data management helps organizations understand how environmental conditions and user behavior can affect the performance of their products. IoT sensors can also be used to measure product performance metrics. The data collected by these sensors can be used to improve future versions of products. Such metrics can help identify possible glitches, future customer requirements, and potential failures in products.

Asset Wear-and-Tear

Generally, organizations have to frequently allocate resources for inspecting wear-and-tear in different assets. Organizations schedule repairs for certain assets and equipment if needed. However, some possible defects may not be discovered during audits. In this scenario, IoT sensors can monitor various aspects of equipment such as vibrations, heat, and moisture in real-time. Thus, businesses can carry out predictive maintenance of their assets to avoid possible failures and downtimes. Using real-time monitoring, businesses can also understand whether end-users are operating their products in differently than anticipated.

Personalization

Studies suggest that 80% of customers are more likely to purchase products when businesses provide personalized experiences. Therefore, businesses must offer customer-centric personalization to increase their sales. IoT data management techniques can allow business leaders to analyze customer data. With careful analysis, businesses can gain valuable insights into customer behavior. Customer data can be collected over time and paired with machine learning platforms to predict customer needs. For instance, in case a customer orders desserts during a specific time slot using a food delivery app, the app can send various dessert recommendations in that time slot.

2. Challenges for IoT Data Management

IoT infrastructure faces the following challenges during implementation:

Scalability

Data collected using IoT sensors are expected to grow in volume exponentially. Research suggests that IoT devices would generate more than 500 zettabytes of data per year by the end of 2019. Hence, businesses can face a major issue of decreasing storage space in IoT data management. Also, business leaders have to explore how they can share and optimize the gathered data. For this purpose, business leaders can ask themselves the following questions:

• Can the existing infrastructure handle large volumes of data?
• Which platform can be used to manage the obtained data?
• Who can access the collected data?
• What will be the expected rate of data growth over the next five years?

These questions can help business leaders understand infrastructure needs to support IoT data management. Also, rising data volumes can give rise to another issue called data gravity. As the volume of IoT data grows, various applications and functions will start finding value in the data. However, the rising number of applications will increase data volume even more.

Security

The generation of large data volumes can attract cybercriminals, who wish to gain illegal access to crucial data. Several big players such as Google, Facebook, Marriott, and British Airways have been victims of sophisticated cyber attacks. Sensitive data of hundreds of millions of users was compromised in these cyber attacks. Hackers can also target operational data, which could disable critical processes in an organization. Various network vulnerabilities and newly-created malware strains can exploit loopholes in an organization’s security protocol to illegally access data. Hackers can also launch automated cyber attacks to hack into an organization’s network. Additionally, lack of tech-savvy staff may click on phishing emails and download malicious files, exposing sensitive business data.

3. Strategies to Implement IoT Data Management

Business leaders should consider the following steps to create an effective IoT data management strategy:

Identify Use Cases

Before adopting IoT solutions, business leaders must identify potential IoT use cases for various business procedures. For instance, a retailer may use IoT data to understand customer behavior, while a manufacturing firm may use it for predictive maintenance. With this approach, business leaders can make informed decisions while choosing IoT solutions and understand their data storage and management requirements.

Hire Skilled Professionals

To implement IoT solutions and IoT data management successfully, business leaders should hire skilled professionals. These professionals can help in developing and executing effective IoT adoption strategies. Additionally, business leaders can assign project managers for their IoT projects.

Allocate Sufficient Budget

Business leaders need to carefully understand several necessities such as infrastructure and resources for successful IoT data management. By analyzing these requirements, businesses can allocate sufficient budget for their project. In case of shortage of budget, business leaders can collect private investments.

Understand data requirements

Before beginning the data collection process, organizations have to understand which type of data they will require and how much data storage they own. Business leaders need to analyze how different data sets can correlate to one another to utilize available data efficiently and minimize storage requirements. Additionally, developers and business leaders need to collaborate to figure out how collected data can be optimized and integrated with enterprise systems.

Implement Security Protocols

Businesses need to implement a multifaceted approach for data security. For starters, organizations can encrypt their data to ensure data integrity. Organizations should also restrict access to sensitive data by providing data access only to concerned parties. Additionally, organizations must educate their employees about data security.

Educate and Train Employees

Businesses must educate their employees about IoT solutions, their benefits, and IoT data management. For this purpose, organizations can also incentivize educating other employees about IoT. The issues of scalability, security, and data gravity can be addressed more effectively using existing IoT data management platforms. Such platforms can allow businesses to deploy, connect, and scale their IoT infrastructure. Instead of building an IoT infrastructure from scratch, organizations can work with IoT platforms that offer a global footprint and access to IoT devices, cloud infrastructure, and networks. This approach can prove to be cost-effective for small and medium businesses.