Data Governance for Cloud-Based Environments: Ensuring Security and Compliance

Benefits and Challenges of Data Governance in Cloud Environment

Data governance includes the policies and procedures implemented to ensure that an organization’s data is accurate from the start and is adequately handled during entry, storage, editing, access, and deletion. Data governance has the following tasks: It provides the infrastructure and technology, establishes processes and policies, and appoints people (or positions) within an organization responsible for handling and protecting certain data types.

Cloud-based data governance typically includes:

1. Cloud service integration. Data governance in cloud environments involves integrating various cloud services and platforms an organization may use for data storage, processing, and analysis. This may include ensuring that data governance policies are seamlessly applied across different cloud providers or services.
2. Cloud data encryption. Cloud data governance places a strong emphasis on data encryption both in transit and at rest. Data should be encrypted to protect it from unauthorized access, especially when stored or transferred within the cloud.
3. Identity and access management (IAM). Cloud data access controls are critical to supervising who can access and manipulate data within cloud environments. Implementing robust IAM controls helps ensure that only authorized personnel can access sensitive data.
4. Data residency and sovereignty. In a globalized world, data governance in the cloud also deals with legal and regulatory aspects, such as data residency and sovereignty. It ensures that data is stored in compliance with relevant laws and regulations, considering where the data physically resides.
5. Disaster recovery and business continuity. Cloud data governance includes provisions for technological incidents such as data breaches or infrastructure failures, which can disrupt data availability and operations. Data must be protected against data loss or cloud service outages, ensuring data availability at all times.
6. Collaboration and sharing controls. As cloud environments often facilitate collaboration and data sharing, data governance solutions define how data can be shared, who can share it, and under what conditions to maintain security and privacy. Clear policies and agreements should be in place to define cloud data ownership and outline the rights and responsibilities of both the cloud service provider and the customer.

Without adequate data governance, inconsistencies in different systems within an organization can remain unresolved. For example, customer accounts in various departments may each be displayed in different formats. Best practices for data governance can facilitate cloud data integration. We compiled some of the key benefits of data governance framework in cloud environments:

• A data governance framework helps structure how data is handled in your company. It enables standardization and consistency as well as streamlining of processes and practices.
• Data governance tools can help you understand what types of data exist in your organization, how it is used, who uses it, where it is stored, and how it is secured.
• A practical governance framework ensures that decision-makers can access accurate data at all times.
• Ensuring cloud data quality by checking that only high-quality data is stored in an organization.
• Reduces risk by helping organizations make informed decisions based on relevant and timely data.

The purpose of a quality data governance technology is to capture, classify, protect, and analyze all types of data throughout its lifecycle to prevent security risks. Data governance benefits contribute to risk awareness by identifying sensitive information and ensuring its appropriate protection.

However, cloud-based data governance is inevitably subject to specific challenges and risks listed below.

1. Data visibility and control

Cloud ecosystems often lack centralized visibility and control over data scattered across multiple services. For example, a multinational corporation stored critical customer data in various cloud services without cloud data monitoring. 

The lack of supervision resulted in difficulties tracking sensitive data, increasing the risk of unauthorized access. Such cloud data governance challenges can be efficiently addressed by adopting a unified data governance platform with a holistic view and centralized data management.

2. Compliance and data residency

Meeting compliance requirements in different regions poses challenges, as data may be subject to varied regulations. For instance, if you represent a European-based e-commerce company expanding to the U.S., you must navigate the disparities between GDPR and CCPA regulations. Such companies face data governance challenges between two countries, leading to legal complexities and potential fines. In this case, selecting cloud providers with global compliance certifications can help.

3. Cloud data security and privacy

Protecting data from unauthorized access and breaches in cloud environments is a critical challenge. A notorious example is the 2014 iCloud breach, where unauthorized individuals gained access to celebrity accounts, resulting in the leak of private photos and data. Companies must utilize strong encryption and multi-factor authentication (MFA) to enhance data governance for remote work, coupled with continuous monitoring and incident response planning, to address security threats promptly.

How to secure Data in Transit and at Rest

Outsourcing data using cloud computing involves various risks, some of which are higher than with local administration. On a technical level, the following problems can occur:

• Data loss
• No access to data due to network failure
• Lack of separation between different users of a cloud
• Cyber ​​attacks on IT infrastructure

Loss of data and lack of access to the data are not only annoying for cloud users but also essentially make moving all data or applications to the cloud irrelevant. Below you can take a look at three cases of data security breaches in the cloud.

1. Dropbox data breach. In 2012, the popular cloud storage service Dropbox suffered a data breach that exposed the email addresses and hashed passwords of over 68 million users. The breach occurred due to a Dropbox employee’s stolen password, which was used to access a document containing user email addresses. While the passwords were hashed, it highlighted the importance of encryption in cloud storage services.

2. AWS S3 misconfigurations. Amazon Web Services (AWS) S3, a widely used cloud storage service, has experienced several high-profile data breaches due to misconfigured access controls. In one case, a misconfiguration by a defense contractor exposed sensitive U.S. government data on an S3 bucket, emphasizing the need for proper configuration.

3. Capital One data breach. In 2019, a former employee of Capital One exploited a misconfigured web application firewall on an AWS server to gain access to sensitive customer data. This breach exposed the personal information of over 100 million Capital One customers.

Tip 1: Implement end-to-end encryption

• Use strong encryption protocols (e.g., TLS/SSL) to encrypt data during transmission between clients and cloud services.
• Ensure that data remains encrypted during storage by employing encryption at rest provided by your cloud service provider.
• Implement end-to-end encryption for sensitive data, which is encrypted on the client side before transmission to the cloud. This ensures that even the cloud provider cannot access the unencrypted data.

Tip 2: Leverage robust access controls

• Establish fine-grained access controls and permissions to limit who can access, modify, or delete data stored in the cloud.
• Utilize Identity and Access Management (IAM) tools provided by your cloud provider to manage user and service identities and define access policies.
• Implement multi-factor authentication (MFA) for cloud accounts to add an extra layer of security, preventing unauthorized access.

Tip 3: Regularly monitor and audit data

• Set up real-time monitoring for data access and changes within the cloud environment using logging and auditing tools.
• Create alerts for suspicious activities or unauthorized access and establish an incident response plan to address security breaches promptly.
• Regularly review and audit your access control policies, encryption mechanisms, and security configurations to ensure best practices for data governance over time.

By implementing these strategies, you can enhance data security within a cloud environment, safeguarding sensitive information from potential threats and thereby ensuring compliance with governmental regulations.

Data Protection Regulations to Comply with

Data protection is essentially about protecting information that is not intended for the general public. It includes personal and private data, for which we have provided examples below.

Personal data:

• Cloud-based email content: personal emails, attachments, and contact lists.
• Cloud-stored electronic health records (EHR): patient health records, medical history, and test results.

Private data:

• Cloud-stored financial records: bank statements, tax returns, and investment portfolios.
• Confidential business plans: strategic plans, intellectual property, and financial forecasts.

Cloud compliance framework is crucial to ensure that personal and private data is secure and access is restricted to authorized individuals while protecting the privacy and security of individuals and organizations. The location of the cloud provider plays a pivotal role in determining which data protection laws apply. Whether the provider is situated within the European Union (EU) or in non-EU countries (USA) has a significant impact on data protection requirements.

Within the EU, the General Data Protection Regulation (GDPR) has been in effect since May 25, 2018, governing the storage of personal data. Storing data in a cloud environment falls under «order processing,» as outlined in Section 28 of the GDPR. This concept is related to the earlier regulation known as «order data processing,» detailed in Section 11 of the Federal Data Protection Act (BDSG), predating the GDPR’s implementation.

According to the GDPR, data governance strategy must comply with a whole range of requirements when using cloud services, such as the following:

• Data processing agreements: establish clear data processing agreements with cloud providers to define data protection responsibilities.
• Data security: implement robust security measures within the cloud environment, including encryption and access controls.
• Consent and transparency: obtain informed consent for data processing and provide transparent information about data practices.
• Data subject rights: enable individuals to exercise their rights, such as access and data deletion, even within the cloud.
• Data breach notification: promptly report and address data breaches in the cloud, notifying authorities and affected individuals.
• International data transfers: ensure compliance with GDPR requirements for international data transfers, which may involve using certified cloud providers or contractual clauses.

If a violation of the GDPR occurs, high claims for damages can quickly arise. To avoid costly outcomes, you may request an audit from a company with deep expertise in data engineering services.

• Master data management. To base your business decisions on data, you must ensure that the data is accurate and consistent.  Prediction models can only make correct predictions if they have been trained with the right data. In the digital world, companies are more dependent than ever on high-quality data to establish new services and products on the market. Therefore, companies will continue to rate master data and data quality management as the most crucial issue within cloud-based data governance processes.
• Data discovery and visualization. Data discovery ranks as a top priority on the task list for multiple organizations at the moment. It helps users discover specific patterns and trends in the data using self-service functionality. Thus, businesses will prioritize advanced analytics methods to examine the data sets. 
• Self-service analytics. The need for self-service functionalities in data governance for data lakes remains high. Companies are now focusing less on providing self-services to meet the needs of individual departments. Instead, they aim to democratize data access across the company. The associated goals for data governance automation will be to create reports as timely as possible and to ensure consistent results.

The Crucial Role of Data Governance in Serverless Environments

To conclude, managing the entire data lifecycle, from creation to deletion, is essential to prevent data clutter and ensure that data is retained or disposed of as required by regulations or internal policies. 

• Ensures data accuracy, security, and compliance, as it directly impacts the reliability of serverless applications.
• Enables seamless integration with various cloud services and promotes efficient data processing.

If you want to use cloud storage as a company, you should pay close attention to data protection when selecting the provider and solution. Especially for providers from third countries, GDPR-compliant processing of personal data is generally not guaranteed. The decisive criteria for a check: where are the provider’s server locations? How is personal data, especially sensitive data, handled according to the data protection declaration?

Without proper data governance and risk management in serverless environments, organizations are at risk of security vulnerabilities and regulatory non-compliance. To develop a tailored cloud data loss prevention strategy, consult a Lightpoint expert today.