Everything You Need to Know About Shadow Data

If you’re unfamiliar with the term, shadow data is simply data that exists on a company’s systems but is not properly managed or monitored. This can include everything from personal employee data to customer information. While it’s not necessarily bad, shadow data can pose a severe security risk if not adequately protected. This blog post will tell you everything you need about shadow data and how to keep it safe. 

What is shadow data, and where does it come from?

Shadow data is data that is created and stored outside of traditional IT systems. It often includes personal and sensitive information, such as customer records, financial data, and health information. Shadow data can come from various sources, including personal devices, cloud-based applications, and social media. 

 While shadow data can provide organizations with valuable insights, it can pose a significant security risk if it falls into the wrong hands. Organizations must put strict security controls, such as data encryption and access restrictions to protect shadow data. They also need to create procedures for monitoring and managing shadow data. By taking these steps, organizations can help ensure their shadow data is safe and secure.

How does shadow data affect businesses and consumers alike?

Most of the people are aware of the importance of data privacy, but they may not realize that businesses are also at risk of data breaches. In addition to the traditional data that businesses collect, there is also a growing amount of so-called “shadow data” that can be just as valuable to hackers. This includes social media posts, online shopping records, GPS location data, and smartphone activity. As more and more businesses increasingly rely on this shadow data, they become more vulnerable to attack. 

In addition, consumers are also at risk of having their personal information exposed. Even if they are not the target of a data breach, the shadow data companies hold about them can be mishandled or sold without their consent. As a result, both businesses and consumers need to be aware of the risks associated with shadow data.

What dangers are associated with shadow data, and how can they be avoided or mitigated?

Shadow data refers to the data outside an organization’s traditional data management processes and controls. While this data can provide valuable insights, it can pose significant risks. For example, shadow data may contain sensitive information that unauthorized individuals could access and misuse. 

Additionally, shadow data may not be subject to the same security and compliance standards as other data within an organization, creating compliance risks. Finally, shadow data can make tracking and managing changes challenging, leading to errors or inaccuracies.

To avoid these risks, organizations need to take steps to address shadow data. For example, they should develop policies and procedures for managing and securing shadow data. Additionally, they should ensure that Shadow Data is subject to the same security and compliance standards as other organizational data. By taking these steps, organizations can minimize the risks associated with shadow data.

Several ways to identify and quantify the value of shadow data: 

1. Use business analytics tools to find unused or underutilized datasets; 
2. Conduct a data discovery exercise to uncover hidden gems; 
3. Calculate the financial impact of lost opportunities associated with unused or underutilized datasets. 

How can you protect your shadow data?

As many businesses move their data online, the risk of data breaches increases. One type of data that is often overlooked is shadow data. Shadow data is any information that is not currently being used but could be accessed by unauthorized individuals. This could include old files, backups, and even deleted data. While shadow data may not be actively used, it can still contain sensitive information that could be utilized to exploit your business. As such, it is essential to take steps to protect your shadow data.

One way to protect shadow data is to encrypt it. This will make it difficult for anyone who accesses the data to read it. Additionally, it would help if you considered storing shadow data in a secure location, such as a private cloud or an on-premises server. Finally, it would help if you put in place strict access controls to ensure that only authorized people can access the shadow data. By taking these steps, you can help to protect your business from the risks posed by shadow data. 

Conclusion

Shadow data is a term used to describe the massive amounts of data that organizations collect and store but never use. Shadow data can include customer contact information for proprietary product formulas. The existence of shadow data often goes unnoticed by companies because it’s scattered across different silos and storage systems. The value of shadow data is increasing as big data sets become more common. 

Also Read: What Are An Event Driven Model And Its Applications With Benefits.