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Data Governance

Collibra supports all CDMC capabilities and offers more

When moving to the cloud, the benefits of availability, cost saving, scalability, reliability, and security are your biggest concerns. The planned move can be quite challenging, depending on how the stakeholders accept the change and how the organization approaches the cloud adoption process.

The success of the cloud initiative depends on a well-defined strategy and a set of proven best practices. The EDM Council’s Cloud Data Management Capabilities (CDMC) Framework offers these best practices as a set of key controls guiding you to select the right approach for your cloud adoption.

What is the CDMC Framework?

The Cloud Data Management Capabilities (CDMC™)  is the best practice framework for the migration, management, and enablement of sensitive data in Cloud. 

Its objective is to build trust, confidence, and dependability for adopting cloud technologies, benefitting cloud service providers, consumers, application and data providers, consultants, and system integrators, as well as regulators.

Organizations face the typical cloud challenges in complexity and mix of data providers, cloud implementation planning, and managing sensitive data. Considering the growing importance of data privacy regulation compliance and strict control of sensitive data, they need to focus on the following data:

  • Personal Information (PI) and Personally Identifiable Information (PII)
  • Healthcare, financial, and other non-public information
  • Confidential business and legal information
  • Other sensitive information 

CDMC best practices focus on the hybrid-cloud implementation to meet regulatory obligations and accelerate trusted cloud data adoption. CDMC defines the required controls and associated capabilities organizations must provide to ensure the secure, compliant storage and use of sensitive data.

CDMC is a standalone framework built on a complex set of six data management components and 14 key controls for managing data risk.   

  • 1.0 Governance & Accountability – ensures the foundation of well-governed business cases, effective data ownership, governance of data sourcing and consumption, and management of data sovereignty and cross-border data movement risks.
  • 2.0 Cataloging & Classification – ensures that data managed in the cloud is easily discoverable, readily understandable, and supports well-controlled, efficient data use and reuse.
  • 3.0 Accessibility & Usage – ensures that data access, use, and outcomes of data operations are done in an appropriate and ethical manner.  
  • 4.0 Protection & Privacy – ensures that all sensitive data has adequate protection from compromise or loss as required by regulatory, industry, and ethical obligations.
  • 5.0 Data Lifecycle – ensures that data quality in cloud environments is managed across the data lifecycle.
  • 6.0 Data & Technical Architecture – ensures that data movement into, out of, and within cloud environments is understood with the architectural guidance on key aspects of the design of cloud computing solutions.

Each of these components have their specific key controls as illustrated in the following figure. 

What the CDMC framework means for your organization

The CDMC framework expands on capabilities that are critical to the control of sensitive data. If your organization collects, stores, uses, and shares sensitive data, the CDMC framework can help you establish compliant controls.

The Gartner 7th Annual CDO survey reports increased focus on monetizing data assets, providing verifiable value to the organization, promoting access to the right data aligned to the business cases, adapting quickly to changing business conditions, and developing innovative products or services. If your organization is aiming for successful cloud initiatives, the CDMC framework can help you leverage cloud benefits in a compliant way. 

The framework assumes that you have a strong foundation of data management capabilities. Its primary purpose is to highlight areas where the features of modern cloud platforms provide opportunities for standardization and automation.

Using the CDMC framework can help you streamline the cloud adoption process, identify and analyze the required components, and evaluate suitable tools. As cloud, multi-cloud, and hybrid environments increasingly drive organizational data management, CDMC can serve as your go-to reference set of capabilities. 

How Collibra supports all the CDMC requirements

Collibra Data Intelligence Cloud completely meets the capabilities requirements of the most recently updated Cloud Data Management Capabilities (CDMC) Framework, 2021.

With an intelligent approach to data, the cloud-native, scalable, flexible, secure, AI-driven platform delivers trusted insights to drive business innovation. Integrating Data Catalog, Data Governance, Data Privacy, Data Lineage, and Data Quality & Observability into a single comprehensive offering, Collibra can automate processes, build trust in data, and scale as your business grows.

The following diagram provides an overview of how Collibra Data Intelligence Cloud components map to the CMDC framework components. 

CDMC Framework Component Key Controls under each Component Mapped component of Collibra Data Intelligence Cloud   Collibra’s Data Intelligence Framework 
1.0 Governance & Accountability
  • Data Control Compliance: monitored for all data containing sensitive data and automated notifications
  • Ownership Field:  data catalog must be populated for sensitive data or reported to a defined workflow
  • Authoritative Data Sources & Provisioning Points: a register must be populated for all data assets containing sensitive data
  • Data Sovereignty & Cross-Border Data Movement: must be recorded, auditable, and controlled for sensitive data
Data Governance

Data Catalog

Data Privacy

 

Pillar: Data Management 

Sub-pillar: Roles and responsibilities 

2.0 Data Cataloging & Classification
  • Cataloging: automated for all data at the point of creation or ingestion, and always on
  • Classification: automated for all data at the point of creation or ingestion, and always on
Data Catalog Pillar: Data Management 

Sub-pillars: Technology, Collection 

3.0 Accessibility & Usage
  • Entitlements and Access for sensitive data: must default to creator and owner, and must be tracked
  • Data Consumption Purpose:  provided for all data sharing agreements involving sensitive data
Data Governance

Data Quality & Observability

Pillar: Data Analytics 

Sub-pillars: Exploiting, Process (of getting access to data)

4.0 Protection & Privacy
  • Security Controls: must be enabled and evidence recorded for all sensitive data
  • Data Protection Impact Assessments: must be automatically triggered for all personal data according to jurisdiction
Data Privacy Pillar: Data Analytics 

Sub-pillar: Process (of getting access to data)

————————
Pillar: Data Literate Culture 

Sub-pillar: Ethics 

5.0 Data Lifecycle
  • Data Retention, Archiving, and Purging:  must be managed according to a defined retention schedule
  • Data Quality Measurement:  must be enabled for sensitive and metrics distributed
Data Quality & Observability Pillar: Data Analytics 

Sub-pillar: Process

————————

Pillar: Data Analytics

Sub-pillar: Data Quality 

6.0 Data & Technical Architecture
  • Cost Metrics: must be available in the catalog, associated with data use, storage, and movement  
  • Data Lineage: information must be available for all sensitive data
Data Catalog

Data Lineage

Pillar: Data Valuation 

Sub-pillar: Revenue

————————

Pillar: Data Valuation 

Sub-pillar: Data assets 

The Gartner 7th Annual CDO survey finds that successful CDOs link data and analytics to prioritized and measured business outcomes. With Collibra, you are not only in control of your sensitive data but also deliver healthier data and trusted insights to drive better business outcomes.

What Collibra offers more with data intelligence

Collibra Data Intelligence Cloud has a deep focus on intelligence about the data, as informed by metadata. As per the IDC definition, data intelligence leverages business, technical, relational, and operational metadata to provide transparency of data profiles, classification, quality, location, lineage, and context, enabling people, processes, and technology with trustworthy and reliable data. 

With Collibra, you can automatically discover and classify sensitive data. The powerful logical data model can be linked to data, and the ML-powered active metadata graphs give rich context to data at scale. Collibra Data Quality & Observability builds trust in data by continuously monitoring pipelines and detecting quality issues before they can hurt.

Collibra has pioneered the data governance category and extended it to create the data intelligence category. It is a cloud-native platform built for business users, supporting multi-cloud with privacy and security by design. It provides the complete stack of data governance, catalog, lineage, quality, and privacy, with APIs for quick integrations.

The 2022 Data Intelligence Index highlights that organizations with the highest data intelligence maturity are seeing 3X better outcomes.  Collibra empowers you to reach that level where the maturity of data science, processes, algorithms, and statistics is used to extract meaning and insights from data. 

How Collibra also supports DCAM (The Data Management Capability Assessment Model)

While the CDMC framework is about the best practices for managing data in the cloud, the EDM council’s DCAM framework focuses on data and analytics management in the organization. When you choose Collibra for CDMC, you also get complete support for DCAM. Organizations typically use DCAM for assessing their data and management foundation and CDMC for controlled cloud adoption.

Go for the best and the only complete solution with Collibra. It is your future-ready single source of engagement for cloud data management.

Want to see Collibra in action?

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