Data

Solutions

Foundation for Monetization - Beyond Compliance

Innovative Yet Pragmatic Use Cases Beyond Compliance to Deliver Value at Scale

Discover how our data governance solutions offer innovative yet practical approaches to drive significant value across various aspects of your data management strategy. Our use cases highlight how we address complex challenges and deliver practical solutions that enhance data governance and utilization.

Data Sovereignty Compliance

Managing data on Cloud

Ensure that your cloud-based data operations comply with global data sovereignty and jurisdictional requirements. Our solutions help you:

Navigate Complex Regulations

Understand and adhere to data sovereignty laws across different regions.

Implement Geo-Restrictions

Control where your data is stored and accessed to meet jurisdictional requirements.

Automate Compliance Processes

Use automated tools to ensure ongoing compliance and audit readiness.

Ensure Data Privacy

Protect sensitive data in accordance with local and international privacy laws.

Active Metadata Management

Driving Data Discovery and Analytics on Modern Data Platforms

Enhance your data discovery and analytics capabilities through advanced metadata management

Dynamic Metadata Capture

Continuously capture and update metadata for improved data visibility.

Contextual Data Understanding

Gain deeper insights into data context and relationships to support effective analytics.

Enhanced data Discovery

Utilize metadata to streamline data search and retrieval.

Automated Metadata Enrichment

Leverage AI to automatically enhance metadata for richer data profiles.

GDPR, CCPA and Other Regulatory Standards

Complying with Data Collection, Storage, Processing, and Deletion

Achieve compliance with key regulatory standards to safeguard data privacy

Data Collection and storage

Implement practices to ensure lawful data collection and secure storage.

Data Processing

Comply with regulations regarding data processing activities.

Data Deletion

Follow legal requirements for data retention and deletion.

Regular Audits

Conduct periodic audits to ensure ongoing compliance with GDPR, CCPA, and other standards.

DCAM & CDMD Standards

Aligned Data Governance Operating Model

Adopt industry-leading data governance frameworks to optimize your data management practices:

DCAM

(Data Management Capability Assessment Model) Align with best practices for data management capabilities.

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(Cloud Data Management Capabilities) Ensure effective cloud data management and governance.

Model Alignment

Integrate these standards into your data governance operating model for comprehensive oversight.

Data Sharing Agreements, Contracts & SLAs

Facilitating Seamless Data Movement Across Boundaries

Streamline data sharing and movement with robust agreements and contracts

Data Sharing Agreements

Establish clear agreements for data sharing across different entities.

Data Contracts

Define terms and conditions for data use and protection.

Service Level Agreements (SLAs)

Set and monitor performance expectations for data-related services.

Integrate Data Risk Management Practices

With a Broader Enterprise Risk Management Framework

Embed data risk management within your enterprise risk management strategy:

Comprehensive Risk Assessment

Evaluate data-related risks as part of your broader risk management framework.

Mitigation Strategies

Develop and implement strategies to address identified data risks.

Continuous Monitoring

Monitor data risks and update strategies as needed.

Govern Unstructured Data

Automating Privacy and Security Management

Manage unstructured data with automated solutions to ensure privacy and security

Automated Privacy Controls

Implement automated privacy management for unstructured data.

Security Measures

Apply consistent security practices to protect unstructured data.

Compliance Tracking

Monitor compliance with privacy and security requirements.

Adaptation of Data Mesh

Decentralizing Data Ownership and Improving Access

Transform data management with a data mesh approach:

Decentralized Ownership

Distribute data ownership across different teams or departments.

Enhanced Access

Improve data accessibility and collaboration within the organization.

Scalable Solutions

Implement scalable data mesh practices to support organizational growth.

Master Data Governance Framework

Regular Reviews and Updates

Maintain an effective master data strategy through continuous improvement:

Framework Updates

Regularly review and update the Master Data Governance Framework.

Strategy Evaluation

Assess and refine your master data strategy to align with business goals.

Governance Practices

Implement best practices for ongoing governance of master data.

Data-Driven Culture

Formulated Enterprise Data Policies and Standards

Foster a data-driven culture within your organization:

Enterprise Data Policies

Develop and enforce policies that promote data-driven decision-making.

Standards & Guidelines

Establish standards and guidelines to support data literacy and usage.

Cultural Transformation

Encourage a culture that values data and leverages it for strategic advantage.

Data Value Realization Framework

Identifying, Measuring, and Maximizing Data Value

Unlock the full potential of your data assets with a structured approach:

Value Identification

Identify opportunities to derive value from data assets.

Measurement Metrics

Measure the impact and value of data initiatives.

Maximization Strategies

Implement strategies to maximize the value derived from data.

Effective Change Management

Leveraging ADKAR for Governance

Manage change effectively within your data governance initiatives:

ADKAR Model

Utilize the ADKAR framework (Awareness, Desire, Knowledge, Ability, Reinforcement) to guide change management efforts.

People-Centric Approach

Focus on the human side of change to ensure successful adoption and implementation.

Continuous Improvement

Adapt and refine change management practices as needed.

AI Governance Frameworks

Addressing Data Bias, Privacy, Security and Ethical Considerations

Implement robust AI governance practices to ensure responsible AI use:

Clear Policies

Develop clear policies to govern AI projects and data use.

Roles and Responsibilities

Define roles and responsibilities for AI governance.

Ethical Considerations

Address data bias, privacy, and security issues in AI initiatives.

Data Quality Framework

Role-Based Access Control and Domain Separation

Ensure high data quality through effective access and domain management:

Domain Separation

Separate business domain groups to manage data quality and access effectively.

Roles-Based Access Control

Implement access controls based on user roles and responsibilities.

Quality Metrics

Monitor and enforce data quality standards across domains.

Ready to Transform Your Data Management practices?

Transform your data management practices with our expert services. Contact us today to learn how we can help you achieve excellence in data governance, quality, and observability.