Data lakes have become essential tools for businesses in the era of Big Data. But keeping those data lakes secure has never been more important as cyberthreats are constantly on the rise. Here’s everything you need to know about data lake security and how Immuta can be an essential partner in keeping your data secure.
To understand how data lakes are secured, it’s important to understand exactly what data lakes are. According to Amazon, a data lake is a ‘centralized repository in the cloud that allows you to store all of your structured and unstructured data at any scale.’
Essentially, a data lake is built to store a large volume of data so that it can be accessed and processed later in its original format. The use of a data lake means that all types of data can be stored using a variety of workloads, including both structured and unstructured data.
Whereas many enterprises once kept their data lakes at on-premise data centers, they’re now being moved increasingly to the cloud because it’s both more economical and more flexible for storage and computing.
However, that brings security concerns. As more data, tools, and users are added, risk of security breaches and the need for enhanced access control rise as well. Lacking fine-grained access control when it comes to the various types of data stored in a data lake can become a major point of concern for businesses.
The result? The increased agility that comes from use of a data lake is neutralized by the inefficiency of poor data lake security and governance.
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Data lake security provides a defined, concrete set of policies and practices that both protect your data lake from unauthorized access and create an efficient access system that doesn’t slow down your processes. Data lake security protocols must also account for compliance with major regulatory policies.
Generally, data lake security policies fall into the categories of authorization, encryption, and authentication.
Authorization determines who within your organization is permitted to access the data lake, and the extent of their access. For example, one individual may be permitted to view and edit the data lake, while another may only be permitted to view it. These authorizations can be based on roles or other traits.
Encryption is the scrambling of data so that only those who are authorized to access it can understand and use it. In data lake security, encryption is essential at every level.
Authentication is a means of verifying the identity of someone attempting to access a data lake and determining whether they have permission to do so. Authentication methods can include passwords and usernames, multiple-device authentication, and more.
But is there more you can do to ensure data lake security?
At Immuta, we’ve perfected a range of best-practices that make data lakes as secure as possible against breaches, accidental data loss or destruction, and improper access. Here are some of the most common methods we use.
Isolation is the foundation of any cloud security. Its purpose is to restrict the capabilities of each cloud platform only to the functions it’s designed for, and no more. Roles for accessing the data lake should be limited to skilled and deeply experienced administrators, minimizing the risk of breaches.
Hardening your data lake platform means using a series of techniques that separate the functions of your data lake from other cloud services. For example, you should follow the configuration settings that are described in detail by the Center for Internet Security when it comes to securing your Amazon Web Services account.
Host security, or host-based security, protects the host from deliberate attacks, and is often the last thing standing between your data and malicious actors. Host security can include host intrusion detection, file integrity monitoring, and log management.
In order to provide the right level of data access control for data lakes, you’ll need to create a strong basis of identity management. Whatever your identity management tool, you’ll want it to be tightly integrated into your cloud services platform.
We mentioned encryption earlier, but it bears repeating that encryption is absolutely fundamental to data security, including data lakes. You’ll want to have encryption established both for data that’s moving as well as data stored at rest. Another important factor you’ll need to address in encryption is certificate rotation.
Data loss can be devastating for any business, which is why robust data loss prevention is an essential best practice. Invest in redundant storage and high availability, and any tools that will allow for immediate rescuing of accidentally deleted data or data that’s been accidentally replaced. Make data loss prevention an essential evaluation tool when assessing any data storage service.
Many organizations now use multiple cloud services to serve individual needs. For example, they might use a service such as Databricks for their data science and ETL platform, but use Snowflake as their BI platform. So how do we help ensure data lake security across Databricks and Snowflake or other cases of multiple platforms?
We provide a consistent way to automate the steps required across both platforms, reducing redundant processes and allowing users to handle more data, more users, and more cloud service platforms without reducing their efficiency.
Using Immuta’s policy builder, for example, you can create a global masking policy and apply it across all fields and across both Databricks and Snowflake uniformly. This includes everything from hashing and regular expression to rounding, conditional masking, and more.
Want to learn more about how Immuta masks and protects data across Databricks and Snowflake? Read more here!
If you’re ready to discover how Immuta can serve all of your data security needs, request a demo today.
