Addressing Key Challenges When Adopting Enterprise Cloud Data Lakes

Enterprises are storing structured, semi-structured, and unstructured enterprise data in robust cloud-based data lakes to reduce infrastructure costs, while scaling-up with ease. However, cloud-based enterprise data lake has its challenges, which enterprises can address by adopting the best practices in data lake management.  

Aligning enterprise goals with data lakes

Enterprises that align data lake creation with key business objectives can benefit from enhanced productivity and increased connectivity that data lakes provide. It is important to develop a comprehensive proof of concept for your enterprise and leverage data lakes for specific applications to acquire maximum enterprise insights.

For example, banking institutions complying with global data management standards (GDPR, PCI DSS, etc.) need to ensure that their data lakes have the right controls for regular analysis and reporting. It is critical to understand the needs of the bank’s managers, project heads, chief information security officers, etc. as well. Data lake leaders, including Impetus Technologies, recommend that firms focus on the most relevant benefits while developing cloud-based data lakes for their enterprises. 

Integrating comprehensive cybersecurity measures

Non-secure data lakes are vulnerable to breaches and hacking attempts as they have not been designed with cybersecurity best practices in mind. Encryption is a key tool to protect the data stored within data lakes, along with firewalls present to protect incoming data packets.

While many platforms provide comprehensive security features, such as after a Hadoop or Snowflake migration, firms must initiate proprietary measures to ensure end-to-end protection. Additionally, enterprises must have a robust employee training and compliance program to ensure that social engineering, crypto-jacking, spoofing, and phishing breaches cannot be executed.

Effective data management and control

A key challenge impacting cloud data lake adoption is the formation of data swamps and mismanagement of user access. Maintaining data access control (DAC) and stakeholder identity and access management (IAM) are crucial as they allow relevant users to access files securely while ensuring dynamic obfuscation of sensitive information within files.

Controlling data leaks on the cloud is critical as well, by ensuring that applications, users, vendors, and external systems are completely secured. Perimeter-based control and cloud-native security features can be leveraged to strengthen data lake security. Enterprises that also perform regular maintenance of incoming sources, data sets, and warehouses have better control over their cloud data lakes.