The Biggest Threat to Your Data Lake: Lack of Governance

Enterprises are increasingly turning to data lakes to store and analyze vast volumes of data. But, have you ever wondered if these data architectures are truly safe? Most traditional data lakes within large corporations face a significant threat that often goes overlooked: the lack of effective data governance. Sure, there might exist some rudimentary version of data governance, but it is crucial to know whether it actually keeps your data safe (and your bottom line).

Faulty Governance

A well-implemented data lake can prove to be an invaluable asset to the firm, providing Analytics, machine learning, AI, and more. When data governance is overlooked, the real problems start: the formation of data swamps, security breaches, legal troubles, non-compliance challenges, and more. But why does that happen?

The Root Causes

Lack of Clear Ownership: When no one is explicitly responsible for data quality and security, it’s easy for issues to slip through the cracks. Without clear ownership, data can become inconsistent, outdated, or even compromised.
Inadequate Metadata Management: Proper metadata is crucial for understanding your data, where it came from, and how it should be used. Without it, your data lake becomes a confusing maze of information.
Poor Data Quality Controls: Without a systematic approach to ensuring data accuracy and consistency, your analytics and AI models can produce unreliable results.
Insufficient Access Controls: Weak or non-existent access policies can lead to unauthorized data access, potentially resulting in breaches or compliance violations.
Lack of Data Lifecycle Management: Without proper data retention and purge policies, your data lake can become bloated with outdated or irrelevant information, increasing costs and complexity.

The Consequences

Data Swamps

With a lack of data governance structure, your data lake can quickly turn into an unusable data swamp–a disorganized repository where valuable datasets get buried under several layers of low-quality irrelevant data with mismatched metadata tagging. Such a data lake eventually ceases to provide any value, only to become a cost center to your firm.

Unreliable Analytics

A direct consequence of a data swamp is unreliable analytics. When your data lacks fundamental integrity and consistency, it would only lead to bad analytics and an inaccurately trained AI model. This could lead to faulty decision-making based on incorrect insights.

Security Risks

Inadequate governance leaves your data vulnerable to both internal and external threats. Without proper access controls and monitoring, sensitive information could be exposed, leading to reputation damage and potential legal consequences.

Compliance Challenges

One of many critical issues stemming from a poor data governance framework is the undesired exposure of Personally Identifiable Information (PII) stored within these data lakes. Such breaches are grounds for legal troubles caused by data privacy regulations. Fines for breaching confidential information can have severe consequences—legally, financially, and reputation-wise.

For instance, GDPR fines in Europe mandate corporations pay upwards of €20 million or 4% of total global revenue, whichever is higher.

Building Effective Governance

To maximize your data lake potential, implement effective data governance practices within your organization. Establish clear ownership of data through data stewardship, enforce data quality standards, and create a more granular role-based access control system.

Having a data-first policy within the organization is key. Invest in training your workforce and ensure everyone knows their responsibilities in maintaining good governance. Create a data lifecycle policy that dictates retention and purges to ensure you only hold data that is absolutely necessary. By paying attention to these areas, enterprises can transform their data lakes from liabilities to profit-driving machines while maintaining effective security and data governance.

SOLIXCloud Enterprise Data Lake is an end-to-end governed data lake platform that can be deployed across cloud and on-prem setups. SOLIXCloud Enterprise Data Lake can fit into your existing data workflows seamlessly to ensure governed data operations to make the most of your datasets.

To learn more about SOLIXCloud Enterprise Data Lake, visit our product page

About Author

Hello there! I am Haricharaun Jayakumar, a senior executive in product marketing at Solix Technologies. My primary focus is on data and analytics, data management architectures, enterprise artificial intelligence, and archiving. I have earned my MBA from ICFAI Business School, Hyderabad. I drive market research, lead-gen projects, and product marketing initiatives for Solix Enterprise Data Lake and Enterprise AI. Apart from all things data and business, I do occasionally enjoy listening to and playing music. Thanks!