#data access

By Cliff Potts, CSO, and Editor-in-Chief of WPS News Baybay City, Leyte, Philippines — May 10, 2026 Reporting Under the Digital Services Act (DSA), very large online platforms are expected to provide vetted researchers with access to data necessary to study systemic risks. YouTube has publicly stated that it supports independent research and has expanded transparency initiatives in response to…

Here are the key takeaways from the blog post regarding your ongoing legal battle with the Income Tax Department. This post will also discuss issues connected to Income Tax Information Evasion & CIC. It is completely understandable why an information seeker feels this situation is both contradictory and unjust. For six years, the Income Tax Department considered these transactions as yours. They…

The effectiveness of modern analytics is fundamentally rooted in how information is accessed and governed. While many organizations struggle with fragmented systems and "gatekeeper" bottlenecks, true data democratization requires a shift toward structured, intuitive access models. When data access is treated as a strategic capability, analytics teams can operate independently, reducing the reliance on IT intermediaries and accelerating the transition from reactive reporting to proactive strategy.

Achieving this level of analytics readiness involves more than just deploying new tools; it demands a balance between accessibility and security. Key strategies for empowering enterprise analytics include:

Policy-Driven Democratization: Moving away from ad-hoc manual permissions to standardized, role-based access integrated directly into the platform. This ensures users have the right level of access at the right time without compromising compliance.

Architectural Decoupling: Separating storage, processing, and access layers. This allows diverse tools to consume the same governed datasets, ensuring semantic consistency and a single version of the truth across the organization.

Metadata-Driven Discovery: Utilizing automated catalogs and quality indicators so users can discover and trust the datasets they need. This transparency reduces the risk of "shadow systems" where teams extract unmanaged data into spreadsheets.

Embedded Governance: Transitioning from restrictive manual reviews to automated policy enforcement. By making governance invisible yet pervasive, organizations can maintain strict security and GDPR standards without slowing down the speed of insight.

Ultimately, sustaining a self-service ecosystem requires treating data access as a product. By focusing on automated remediation and domain-aligned ownership, enterprises can pay down technical debt and build a resilient foundation for advanced use cases like AI and real-time predictive modeling. Organizations that prioritize this structured access patterns consistently see higher adoption of their analytics platforms and faster, more confident decision-making across all functional departments.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in Democratizing data means balancing self-service with governance. Here’s how leaders can build trust while empowering innovation. Data is no longer locked in silos or reserved for analysts. It is the heartbeat of modern business. The call to democratize data is reshaping how firms operate—empowering employees across roles to…

In a world where data has become the new oil, cloud computing has emerged as the go-to technology for businesses to store, process, and access their valuable information. From small startups to global corporations, cloud computing has enabled organizations to leverage the power of remote computing resources, improve productivity, and reduce costs. However, with the vast amount of data being stored on the cloud, managing access to data has become a global challenge. From data breaches and cyber attacks to regulatory compliance and data privacy, companies around the world are grappling with these challenges to ensure the security and privacy of their data.

With the increased usage of cloud computing, organizations are now dealing with the complex process of managing and controlling who has access to their data. They must ensure that only authorized personnel have access to sensitive data, while also making sure that their data is secure from cyberattacks, data breaches, and other malicious activities. Additionally, they must ensure that their data complies with existing regulations and laws regarding data privacy.

This is like trying to walk a tightrope. Organizations are balancing the need to provide access to the right people while also ensuring that all of the data is secure and compliant with the relevant laws and regulations. One misstep can have serious repercussions, so they must be very careful.

In this blog, we will explore the greatest challenges of managing access to data on cloud computing and how organizations around the world are tackling these challenges to safeguard their data and stay ahead in today's digital economy. So, let's dive into this global conversation on managing access to data on cloud computing and discover how businesses around the world are adapting to the new reality of data security in the cloud.

Oh! Wait before we move forward to the topmost challenges, fist let’s understand… 

What Is Data Access Management in the Cloud?

Data access management (DAM) is a process that governs the access, modification, and sharing of data stored in a cloud platform. It is a critical element of data security and compliance for cloud-based applications and services. DAM ensures that only authorized users, processes, and applications are able to access, modify and share data stored within the cloud. It also helps protect the data from malicious attacks, unauthorized access, and unauthorized changes. 

Additionally, it ensures that data remains compliant with industry and regulatory standards. To ensure effective data access management, organizations must implement the right security measures, such as authentication, authorization, encryption, and other measures to protect data. Additionally, organizations must have processes in place that dictate when and how data can be accessed, modified, and shared. This will help ensure data is accessed responsibly and in accordance with any applicable laws or regulations. Organizations must also ensure that data access policies and procedures are reviewed regularly to ensure they remain up-to-date and effective. Finally, organizations must also monitor access to data to identify any potential security threats, unauthorized access attempts, or malicious activity.

To delve deeper into these challenges, let us take a closer look at each of them:

1. Complex Infrastructure: Cloud computing requires complex IT infrastructure, which can lead to difficulty managing data access.

2. Limited Visibility: Companies often have limited visibility into the security of their data in the cloud, which can leave them vulnerable to unauthorized access.

3. Lack of Control: Companies often need help to control who has access to their data in the cloud, making it difficult to ensure data security.

4. Data Protection: Companies must ensure that their data is protected from vulnerabilities in the cloud, including malicious actors and hackers.

5. Data Breaches: Data breaches can occur in the cloud, leading to a loss of confidential data and potential legal liability.

6. Costly Resources: Cloud computing can be expensive due to the specialized infrastructure and personnel necessary to maintain it.

7. Regulatory Compliance: Companies must ensure that their data is compliant with applicable laws and regulations.

8. Data Loss: Data stored in the cloud can be lost or corrupted due to outages, malicious attacks, and human error.

9. Privacy: Companies must ensure their data is secured and protected from unauthorized access.

10. Scalability: Companies must be able to scale their cloud infrastructure to meet changing needs.

Conclusion