If your organization has significant amounts of sensitive data stored in your network, it can be difficult to store it properly. Your network may have security vulnerabilities that can lead to data breaches and cyberattacks.
These attacks can result in compromised data, leading to damaged business reputations, legal consequences following broken compliance, lost customers, and lost revenue.
In addition to these consequences, it will cost hundreds of thousands and potentially millions to repair your network following an attack. For these reasons, reliable data management should be prioritized.
No organization can operate effectively with data being compromised. It is important to have reliable data management to store data efficiently and securely.
COEO understands how important data management is and has helped thousands of organizations improve their data storage to secure it more efficiently and improve security.
By the end of this article, you will understand what IoT data management is, its key features, best practices, and whether using IoT data management would be beneficial for your organization.
What is IoT data management?
IoT data management is the process of collecting, storing, and managing data stored in a network, generated by devices connected to the network. IoT data management uses technologies and policies to ensure data is accurate, secure, and accessible to employees.
This ensures that employees can use the data for informed decision-making and process optimization.
IoT data management ensures that every byte of data stored on the network will be protected throughout its life under set policies and standardized practices.
The key features of IoT data management
IoT data management can help organizations improve data management and security. However, understanding its key features will help determine whether it is appropriate for your organization. The features of IoT data management include:
Data quality management
IoT data management ensures data quality to organizations. IoT data management uses data quality processes to ensure data is stored and transmitted without losing accuracy or data points at whatever volume the system requires.
Adding extra data error correction, ensuring lossless data transmissions, and building large-scale data storage systems capable of handling a very high volume of data transmission and storage are all ways that IoT data management can incorporate data quality management.
Information lifecycle management
Another feature of IoT data management is information lifecycle management, which incorporates knowing where data streams are coming from and the volume of data in the stream.
Information lifecycle management also helps guide data streams to where they should be stored and makes sure they are archived or deleted when they should be.
Data protection
IoT data management ensures data is protected, requiring data in motion to be encrypted and securing data access in back-end systems.
IoT data management also requires clear policies to be set for the data needs that must be protected and how, as well as identifying the employees who are allowed access to the data based on roles in the company and at what points in the data lifecycle.
Compliance management
Most organizations have rules and regulations for network data based on compliance requirements. These compliance requirements are based on the industry your organization operates in.
For example, if your organization is in the healthcare industry, it must follow HIPAA rules and regulations that are aimed at protecting patient information.
IoT data management is aimed at reliably protecting and managing data, ensuring organizations will maintain compliance with industry rules and regulations.
The best practices for IoT data management
Now you understand what IoT data management is and its key features. However, if your organization is looking to implement IoT data management, it is important to understand its best practices so you can properly implement them into your strategy.
The best practices for IoT data management include:
Understand the volume and variety of data
Before incorporating IoT data management policies, it is important to understand the volume and variety of data that is being stored or that needs to be transferred. This way, you know what to expect when incorporating IoT data management.
Ensure excess capacity in the data management system
Another best practice to consider is ensuring you have excess capacity in all components of the data management system, including processing, encryption, and storage of data.
Ensuring you have capacity in these components enables you to safely work with as much data as necessary.
Apply zero-trust principles to IoT data
Zero-trust is a security method that assumes nothing is trusted on the network.
Incorporating zero-trust on IoT data requires verification from any user looking to access data in the network, ensuring that data will remain secure and help prevent data from being compromised by malicious actors.
Secure IoT endpoints
In addition to applying zero-trust principles, it is important to secure IoT endpoints. Endpoints are any device that connects to the network and stores or transfers data.
Securing these devices by following zero-trust policies and encrypting data in transit and at rest will protect the data and help prevent data from being compromised.
Understanding data compliance requirements
While most organizations have data compliance requirements to follow, these requirements can vary depending on the size of the organization, the industry it operates in, etc.
It is important to understand the data compliance rules and regulations that might apply to your IoT data so that you have appropriate policies regarding your compliance requirements.
Understand the lifecycle of data
Another best practice of IoT data management is understanding when and how data should be removed or archived from the network and active systems. It is important to set these policies so that older data does not take up storage space.
Is IoT data management appropriate for your organization?
Now you understand what IoT data management is, its key features, and its best practices. However, it is also important to understand whether IoT data management is appropriate for your organization.
If your organization has significant amounts of sensitive data transferred to your network and stored from devices, IoT data management may be beneficial to ensure that you can reliably manage and protect the data.
If your organization has data compliance rules and regulations to follow, IoT data management may be appropriate for your organization to remain compliant.
Conversely, if your organization does not store a high volume of data or does not have devices that store and transfer data to the network, IoT data management may not be necessary.
Determining whether your organization should incorporate IoT data management
Now you understand what IoT data management is, its key features, the best practices for the process, and whether it is appropriate for your organization. This will enable you to better determine whether you should incorporate IoT data management.
Organizations that have massive amounts of data stored on the network and on devices connected to the network need to efficiently manage and secure the data so it can be accessed by employees and protected from data breaches.
No organization can afford to have sensitive data compromised from its network. Sensitive data such as patient, customer, or client information can be leaked, resulting in damaged business reputations, lost customers, lost revenue, and financial penalties as a result of broken compliance.
This could cost hundreds of thousands or even millions of dollars. For these reasons, it is important for data to be reliably stored and secure.
COEO understands the importance of reliable data storage and has helped thousands of organizations secure their data to prevent data from being compromised.
We want you to understand what IoT data management is so you can determine whether it would be beneficial for your organization.
If you would like to speak with our team to learn more about data management and security or ask any questions you may have, you can schedule an appointment.
Now that you know what IoT data management is, its key features, and best practices, read this article to understand the challenges with IoT and how to solve them:
