At present, many businesses struggle with their data quality and thus, the need of data lake services come in importance.

A data lake is a centralized treasure trove of raw information in its structured and unstructured manner from a wide variety of sources. The data can be stored as it is, without having to organize it. It enables real-time analytics, reporting dashboards and visualizations, and machine learning for analysts to access information in the data lake directly using advanced tools.

Broadly, a data lake ingests data in its raw form without having to clean, standardize, reorganize or transform it in any way. The early and quick ingestion of data indicates that operational data can be made available to analytics. Furthermore, the original form of data ensures that data scientists, data analysts, and other similar users have access to enough raw information. The raw information can be reassembled in different ways as and when needed accordingly.

Isolate security functions: As a common practice, security functions should be classified and separated from non-security functions and user access should be restricted to the authorized personnel. To isolate security functions is to mitigate breach risks. The isolation will allow users to implement appropriate levels of security mechanisms and operational control. To ensure proper isolation and classification of data, businesses need to evaluate existing data in the data lake and build procedures to analyze upcoming information. Also, this helps users secure data lakes against unauthorized access.

Cloud Platform Hardening: It is highly imperative to isolate and harden your cloud data lake platform beginning from a unique cloud account. With a unique cloud account functioning your data lake, restrict the platform capabilities so that authorized users can only manage and administer the data lake platform. A unique hardened account enhances security by enabling logical data classification & separation from other cloud services. Once the user has established a unique cloud platform to run data lake service, Center for Internet Security (CIS) guidelines can be implemented. This is an efficient and secure way of storing data and performing various business operations.

Identity Management & authentication measures: A strong basis for identity management should be mandatorily created to audit and access control for cloud data lakes. The initial step to secure your cloud data lake is to integrate your identity provider and cloud provider. For certain infrastructure services, integration may be enough for identity. However, to manage your own third party applications or data lakes with multiple sources, you may require integrating a wide variety of authentication services like SAML clients and providers to make use of Kerberos, Auth0, Apache Knox, OpenLDAP, etc. Additionally, authentication measures are required to secure sensitive data and enable data and resource access controls to authorized personnel only.

Host-based security: Host-based security is one of the most critical and overlooked security layers in cloud platforms. Host-based security often works as a protective layer to sensitive information and against cyber attacks. As a broad endeavor, it must adapt to function use cases. With host-security in place, any suspicious activity can be detected easily and it also sends alerts to administrators in case of any unusual activity. The scope of securing a host varies as per service and functional areas. With the introduction of machine learning algorithms, it offers high detection rates to prevent any fraudulent event and meet regulatory compliance.

Network Perimeter Security:

The secure network path you design for your cloud data lake services comprises its first list of defense. There are different ways one can solve the networking perimeter by accounting for their specific circumstances. Some methods will be based on compliance needs or driven by bandwidth that may indicate a cloud-based VPN is needed. If any confidential and sensitive information is stored in the cloud, a firewall becomes crucial to maintain visibility and traffic control. It is advised to leverage third-party next-generation firewalls accessible through your cloud account as they offer highly advanced features like threat intelligence, intrusion prevention, application awareness and complement native cloud security tools. By utilizing such firewalls, one can secure and ensure regulatory compliance across all cloud environments.

Encryption practices: Encryption is common to data security and cloud providers provide best encryption practices. It is important to get appropriate details and doing so requires a strong hold of IAM, encryption key rotation policies, and configuring applications. For logs, volumes, and data storage on AWS, one should have a basic understanding of KS CMK best practices. Encryption practices must secure both data at rest and data in motion and may demand your own certificates. In case of using integrated third-party services, you may require an associated rotation regimen.

Conclusion:

In the industry competition to leverage cloud data lake services and technology advancement, security cannot be overlooked - consistent safeguarding is must. By following best end-to-end security practices, businesses can enjoy benefits of cloud data lakes, while ensuring data remains confidential and completely protected.
To know more about an automated approach to ensure data lake security, book a free session with Polestar Experts today!