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Securing Enterprise -Grade Data Access at Scale

Enabling secure cross-enterprise data access for business productivity and innovation.

By 2025, 30% of Gartner clients will protect their data using a “need to share” approach rather than the traditional “need to know” approach.

As you’re the key stakeholder for data or business innovation at your company, ensuring data security and access is your top priority. 

But when it comes to regulated and sensitive data, it’s hard to be compliant and almost impossible to maintain roles and operational conditions (which are always changing). Compounded by regulatory changes, the emergence of dark data, and duplicated datasets can leave you non-compliant and exposed.

Driving innovation through cutting-edge AI technology will help you open data access, maintain security, and automate policy management. As a result of gaining control of your data, granting access to the right people, and automating compliance, you’ll become a data-driven enterprise, work more efficiently, and generate more revenue opportunities.

On average, data-driven enterprises generate more than 30 percent growth per year.*


Why Fast & Secure Data Access Matters

The speed at which employees gain data access to drive business initiatives is critical but often hindered by cautionary analysis of who can see data based on complex variables and factors. These long lead times paralyze business agility, leading to competitive degradation that impacts revenue and profitability.

However, secure enterprises: 

  • Optimize data security while providing
    access to the right people 
  • Prevent data malpractice
  • Ensure data-driven decision-making
  • Drive business innovation while remaining privacy-compliant

Today, the goal of any enterprise’s data or business innovation department is to strike the perfect balance between security and data utilization, which is a constant challenge. By staying on top of the latest technology and striving to become cutting-edge, enterprises maintain a competitive advantage, quickly adapt to change, enhance efficiency, and establish market leadership.

The Cost of Non-Compliance & Dark Data

On top of that, non-compliance could cost a company’s brand reputation and rack up nearly $15 million in business disruptions, productivity loss, revenue loss, and other fines and penalties. While dark data is estimated to cost businesses worldwide €2 billion each month in storage capacity.

The Traditional Data Access Process Is Broken

Balancing Data Access and Security Is a Challenge

Data departments need to grant appropriate data access to different teams and third-party vendors while minimizing the risk of unauthorized access. While securing data is a top priority, they also understand the need to harness data for analytics, insights, and innovation. Striking the right balance between security and utilization is a constant challenge.

Traditional Data Access Workflows Reduce Enterprise Efficiency and Security

Here’s how a traditional data access workflow would slow down productivity and reduce collaboration:

  1. Data Access Request Submitted
    An employee needs specific data for work purposes and submits a formal request for access. They could make the request through an internal system, email, or form.
  2. Request Lacks Clarity
    The request lacks the right information about why the data is needed or how urgent the request is, so the data department requires clarification.
  3. Manual Routing and Approval Process
    The request is sent manually to various departments or individuals for approval, including managers, data owners, IT, legal, or compliance teams.
  4. Request Delays Due to Backlogs and Priorities
    There might be delays in processing the request due to a backlog of requests, an approval bottleneck or an inability to redact unauthorized data via masking or anonymization.
  5. Complex Approval Process
    Since the approval process is complex and involves multiple stakeholders, finally approving the request may take weeks or even months.
  6. No Standard Process
    Having no standard process or automated system for keeping up with ever-changing regulations, data access requests, handling and tracking requests creates an inefficient workflow. 
  7. Diffused Responsibility and Ownership
    When multiple stakeholders are involved it may not be clear who is responsible for granting access to the requested data, which leads to further delays and confusion as the request is passed through different departments.
  8. Lack of Communication
    Since the employee hasn’t heard anything since they made the request they may follow up and ask for confirmation that the request was received and when they should expect access, if any. 
  9. Manual Data Retrieval Process
    In the case where manual data retrieval is needed, the process may take even longer. 
  10. Final Approval and Access Granted
    After weeks or months of waiting, the employee finally receives the necessary approvals and access is granted. However, the delay has already impacted the employee’s productivity and pushed back their timelines.

Reimagining the Data Access Lifecycle

Shifting how your enterprise secures data access from “need to know” to “need to share” doesn’t just change how your organization works. It evolves how your enterprise analyzes, requests, and uses data to achieve greater insights, innovation and collaboration. Ultimately, reimagining your data workflow will allow your enterprise to meet employee needs faster while safeguarding sensitive information at scale.

Creating a secure and efficient workflow for data access starts by having a tool or platform in place to discover data, manage policies, mitigate risk, actively monitor ever-changing privacy rules and regulations, and automate adhering to these changes without slowing down company productivity.

A Secure Data Access Lifecycle:

  1. A data access request is made
  2. One team identifies and verifies the requester
  3. The data is located and retrieved
  4. The data is reviewed, and unauthorized data is redacted based on policy rules
  5. The data is formatted and delivered 
  6. The request process is documented
  7. The policy catalog is updated 

As of now, many enterprises require multiple stakeholders to complete this process. But what if you could automate steps 2-7 with the right DSP (data security platform) and the help of AI?

Implementing the Right Data Security Platform

A DSP (data security platform) built for enterprises will allow for self-serve data access, faster data verification, automated data redaction based on roles and attributes, and an efficient process for documenting requests to maintain transparency for future auditing.

That’s why Velotix offers a simple yet effective data access lifecycle for enterprises:

The Data Access Lifecyle with Velotix:

  1. Discover Data & Permissions
    Integrate your existing database with Velotix to discover, classify and analyze data so you identify sensitive information and protect it.
  2. Request Access via Self-Service
    Provide your enterprise with one platform where employees can request data and your data department can review requests and make decisions based on AI Recommendations.
  3. Automate Policy Management
    With Velotix, you’ll create a single source of truth by automating and enforcing your policy database in one place.
  4. Share Authorized Data
    Based on policy rules, Velotix will redact unauthorized data, so your data team can grant secure data access in hours not weeks.
  5. Monitor Process 

Since all data requests are happening in one place, your data department can track the data lifecycle, defeat dark data, and ensure policy compliance all from one easy-to-use dashboard.

Powered by AI, Velotix provides indispensable technology by monitoring, learning, and predicting how data will be used to provide the right people with the compliant data they need to fuel data democratization and business success.

— Noam Biran, VP Product at Velotix

Grant Enterprise-Grade Secure Data Access at Scale

Velotix, our AI data security platform, was built to help enterprises provide secure data access at scale. Our use of AI is not an afterthought. It’s our genesis. We use AI and machine learning to discover and organize your data, then automate policy creation and subsequent access control so you remain secure, compliant and agile.

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