Best Practices for Data Lake Security
Modelingcybersecurityposted by Zac Amos May 22, 2023 Zac Amos
In today’s world, digital and computer technology is essential for businesses to operate efficiently. Rather than using paper records, data is now collected and stored using digital tools. However, even digital information has to be stored somewhere.
While databases were the traditional way to store large amounts of data, a new storage method has developed that can store even more significant and varied amounts of data. These are called data lakes.
What Are Data Lakes?
Unlike databases and data warehouses, data lakes can store data in raw and unstructured forms. This feature is important because it allows data lakes to hold a larger amount of data and store it faster.
When data is stored in a database or data warehouse, it has to be processed into a specific format. While this was an exceptional limitation in the past, the rise of cloud computing has dramatically increased the amount of data companies have to process and access regularly.
With the old system, losing some of that data in the formatting process was possible, which could lead to complications if vital parts were missing. At worst, it causes legal ramifications for the company if the data lost is a client’s personal information.
Data lakes have become the preferred storage method of many companies because they do not have to format data to store it. Storing data this way can save processing time and allow companies to access information faster. Increased speed and efficiency can give organizations a competitive advantage in the digital age.
Studies show that 64% of businesses use data lakes as their primary method of storing data because it allows them to get more operational and analytics business value from said data. Data lakes also significantly reduce the need for digital silos and are overall more cost-effective.
Securing Data Lakes
One of the biggest challenges of securing such a large data storage is digital security. As cyberattacks on businesses continue to rise, securing digital assets to prevent data from falling into the wrong hands is more important than ever.
While standard security measures such as passwords, multi-factor authentication, and antivirus/antimalware programs are effective, data lakes also have unique security requirements.
1. Understand Data Lake Management
Having a strategy for managing data lakes will help companies make the best use of their system while also helping to enhance its security. To manage a data lake, organizations should have an understanding of how the data is used, its applications, and how many people have access to the data lake.
The unique nature of data lakes means that their structure becomes increasingly complex the more data they absorb. This complexity can make security harder to manage as the lake gets bigger and more people need access to the data.
Keeping track of who has access to what kind of data and ensuring that they follow proper security measures is essential for securing the data lake. In many cases, this could mean using multiple security programs and platforms.
2. Securing Data Lake Processing
Since data lakes have many security requirements that only get bigger as time passes, most companies apply security measures to each of the main processes rather than one security program to govern everything. Therefore, companies must understand how data moves through a data lake.
There are considered three main layers of the process data lakes use to receive and store new data. Data ingestion is when new data is introduced and absorbed into the lake. The processing layer is when data is managed and sorted into its storage category. Finally, the data output layer stores the data in the appropriate places so users can access it.
Each of these components will require different forms of cybersecurity. The data ingestion layer should involve encryption and data masking protocols. Processing should take measures to limit how many people can access the data — keeping it to only essential users. Data need to be monitored closely once it reaches the data output layer.
3. Keep Visibility High With Constant Monitoring
Data lakes require constant vigilance and transparency to keep them secure. Administrators and security professionals will need to constantly audit security logs and alerts to keep a lookout for potential cyber threats.
As the data lake gets bigger, more security measures must be taken and improved. Being able to constantly adapt to the growing needs of the data lake is essential to securing the organization. Automated security monitoring tools can help in this regard.
Keeping Data Lakes Secure is Essential
Securing data lakes is critical for any company or organization that works with data. As data lakes get bigger, businesses must keep up with their growing security requirements to prevent data breaches. Being able to safeguard the data lakes will keep a company’s livelihood secure.