Risk-Based Classification
Protection requirements vary with data sensitivity, business impact, use and lifecycle rather than one blanket rule.
Data Security Governance
Data Security Framework Consulting for Governed, Traceable Data Protection
DataConsultant helps organisations design a business-led data security framework that connects data sensitivity, risk, ownership, policy, access, encryption, secure sharing, monitoring, incident readiness and control evidence. The engagement turns fragmented security expectations into a practical framework that data owners, security teams, platform teams, risk functions and business leaders can operate across the data lifecycle.
Classification and control requirements linked to business risk
Named owners, decision rights, exceptions and evidence responsibilities
Access, encryption, sharing, monitoring and resilience governed together
Prioritised implementation roadmap instead of a document-only framework
Scope, timing and commercial terms are confirmed after reviewing the data estate, risk context, applicable requirements, evidence, stakeholders, control maturity and implementation needs.
Accountable Decisions
Owners, security, privacy and platform teams know who decides, implements, approves exceptions and supplies evidence.
Consistent Controls
Access, encryption, sharing, monitoring and resilience requirements use one governed control architecture.
Measurable Assurance
Control evidence, exceptions, risks, reviews and improvement actions can be tracked and escalated.
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Why Data Security Breaks Down Without a Shared Framework
Security controls often exist, but the rules connecting data sensitivity, business ownership, technology enforcement and evidence are fragmented. A framework creates the decision system that makes those controls coherent.
Inconsistent classificationDifferent labels and handling rules across teams
Unclear control ownersSecurity and data accountability do not line up
Access sprawlPrivileges accumulate without consistent review logic
Uncontrolled sharingThird-party, export and residency decisions vary
Weak evidenceControls exist but proof is incomplete or hard to trace
Disconnected responseData ownership is missing from incident and recovery plans
Controls vary by platform, project or team
- Classification is incomplete or not linked to control requirements
- Data owners are consulted inconsistently on security decisions
- Access, encryption, DLP and sharing controls use different decision logic
- Exceptions are approved without one risk and expiry model
- Evidence is assembled reactively for audits or incidents
- Security improvements compete without a common prioritisation model
Requirements, ownership and evidence work as one system
- Data categories drive proportionate protection and handling expectations
- Decision rights connect business owners, security, privacy and technology
- Control requirements are reusable across platforms and delivery patterns
- Exceptions are time-bound, owned, evidenced and reviewed
- Monitoring and assurance use defined evidence and performance measures
- Implementation is sequenced by risk, business impact and readiness
Turn Scattered Security Controls Into One Governed Framework
Start with the data risks, control gaps, decision rights and evidence problems that matter most. DataConsultant can help define a practical target framework and the roadmap to operationalise it.
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What the Data Security Framework Service Defines
The service is designed as an operating framework for data protection decisions. It can begin with assessment and design, then extend into control mobilisation, governance activation and implementation support.
A data-specific security operating model, not another generic policy pack
The framework links business purpose and data risk to clear protection requirements. It establishes how data is classified, who owns security decisions, which controls apply, how exceptions are governed, how technology teams translate requirements into implementation patterns, and what evidence shows that controls are operating.
Scope boundaryData domains, systems, jurisdictions, third parties and lifecycle stages in scope
Decision modelOwners, approvers, implementers, reviewers, escalation and exception authority
Control architectureReusable control requirements linked to data classes, risks and delivery patterns
Evidence modelWhat is measured, retained, reviewed and reported for assurance and improvement
01
Discover & classifyIdentify important data, sensitivity, ownership, location, flow and handling context.
02
Protect & authoriseSet access, privilege, encryption, masking, key and handling requirements.
03
Share & transferGovern internal exchange, third parties, exports, remote use and residency considerations.
04
Monitor & assureDefine logging, DLP, control evidence, reviews, metrics, exceptions and assurance routines.
05
Respond & recoverConnect data ownership and criticality to incident, breach, backup, recovery and continuity processes.
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Data Security Framework Capability Map
Each capability works together. The final framework can be narrower or broader depending on the data estate, risk profile, existing controls and decisions the organisation needs to make.
Data inventory, criticality & classificationSensitivity, business impact, purpose, location, lifecycle, ownership and handling categories.
Ownership, policy & decision rightsAccountable data owners, security authority, privacy interfaces, RACI, forums and escalation.
Access & privileged-data controlsLeast privilege, approval, role logic, service accounts, privileged access, review and segregation.
Encryption, keys, masking & tokenisationRequirements by data class and context, with ownership and exception logic.
Data Security
FrameworkOne control model linking policy, owners, technology, evidence and improvement.
FrameworkOne control model linking policy, owners, technology, evidence and improvement.
Secure sharing, third parties & residencyExternal exchange, vendor access, contracts, transfers, approved channels and location constraints.
DLP, logging, monitoring & evidenceDetection objectives, logs, review routines, control proof, metrics, alerts and evidence retention.
Incident, backup, resilience & continuityData criticality, breach readiness, response roles, recovery priorities and continuity dependencies.
Exception, assurance & improvementRisk acceptance, expiry, remediation, testing interfaces, issues, KPIs and framework review cadence.
| Risk / requirement | Framework rule | Accountable decision | Implementation pattern | Evidence | Measure |
|---|---|---|---|---|---|
| Sensitive customer data | Restricted handling class | Data owner approves permitted purposes and recipients | Least privilege, encryption, masking where appropriate, approved transfer channel | Access decisions, configuration evidence, transfer records | Exceptions, review completion, unresolved high-risk access |
| Privileged production access | Elevated access control | System owner and security approve privilege and duration | PAM or equivalent control, strong authentication, logging and periodic review | Approval, activity logs, review record, closure evidence | Standing privilege, overdue reviews, exception age |
| Third-party data exchange | External sharing control | Business owner accepts purpose and third-party dependency | Approved channel, contract/control checks, minimum data, monitoring | Assessment, approvals, contract references, transfer evidence | Unreviewed suppliers, expired approvals, unresolved findings |
| Critical analytical data | Availability and recovery requirement | Business owner validates recovery priority | Backup, recovery testing, resilience and dependency controls | Backup logs, test results, recovery evidence, issue records | Test completion, failed recovery actions, overdue remediation |
Define the Control Catalogue, Owners and Evidence Your Teams Can Actually Operate
Translate security expectations into reusable requirements with clear applicability rules, accountable decisions, exceptions, implementation patterns and measurable evidence.
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Tangible Data Security Framework Deliverables
Outputs are agreed during discovery and are designed to support decisions, implementation and ongoing governance rather than remain as disconnected documentation.
Current-State Security Assessment
Confirmed strengths, gaps, dependencies, evidence limitations, ownership issues and risk themes across the agreed scope.
Target Data Security Framework
Principles, scope, control domains, lifecycle model, governance interfaces and design decisions for the target state.
Classification & Handling Model
Practical data categories with protection, access, sharing, transfer, retention and handling expectations.
Security Control Catalogue
Control objectives, requirements, applicability, owners, implementation guidance, exceptions, evidence and review expectations.
Roles & Decision-Rights Matrix
Accountability across data owners, security, privacy, risk, platform teams, identity teams, stewards and business functions.
Policy & Exception Architecture
Policy hierarchy, standards interfaces, approval authority, risk acceptance, expiry, remediation and governance workflow.
Evidence & KPI Framework
Control evidence, review cadence, leading and lagging indicators, reporting, assurance inputs and management escalation.
Prioritised Implementation Roadmap
Sequenced improvements with accountable owners, dependencies, decision gates, enabling work and mobilisation backlog.
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Standards and Regulatory References Used as Design Inputs
The framework can map to recognised security and regulatory references when they are relevant to the organisation. These references inform control traceability; they do not turn the engagement into legal advice, certification or statutory assurance.
ISO/IEC 27001:2022
Can be used as an ISMS requirements reference for risk-based security management and for aligning data-security governance with the organisation’s wider information-security system.
Official ISO referenceNIST CSF 2.0
Can provide outcome-oriented cybersecurity structure across Govern, Identify, Protect, Detect, Respond and Recover, with the data framework adding data-specific ownership and control detail.
Official NIST referenceDPDP Act 2023 & Rules 2025
Where applicable, the framework can support security-control and evidence readiness for digital personal data while authorised specialists validate current commencement, legal interpretation and obligations.
India Code Act referenceCERT-In Directions
Where applicable, incident reporting, logging and related cybersecurity-direction interfaces can be considered in the framework and validated against current CERT-In requirements.
Official CERT-In referenceRegulatory applicability varies by organisation, sector, data, jurisdiction and date. DataConsultant can structure requirements, controls, evidence and ownership to support readiness, but legal conclusions, formal certification and regulated assurance must be provided by appropriately authorised specialists.
Identity & privileged accessIAM, IGA, PAM, role models, service accounts, approval and recertification workflows.
Cloud & data platformsCloud IAM, databases, warehouses, lakehouses, storage, analytics workspaces and APIs.
Protection & monitoringEncryption, key management, secrets, masking, tokenisation, DLP, logging and security monitoring.
Governance & evidenceCatalogues, lineage, ticketing, risk systems, evidence stores, backup/recovery and reporting tools.
Map Framework Requirements to Your Data, Cloud and Security Estate
Connect the target control model to the platforms and teams you already operate—without turning a governance framework into a vendor-led product selection exercise.
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Operating Model and Decision Rights for Data Security
Security requirements only become repeatable when business ownership, security authority and technology execution are explicit. The operating model makes those responsibilities visible.
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How the Data Security Framework Engagement Works
The sequence is adapted to the scope and evidence available. Numeric duration is confirmed only after the organisation, control boundaries, stakeholders, review cycles and implementation depth are understood.
01
Align
Confirm objectives, sponsors, decision questions, boundaries, risks and success criteria.
02
Discover
Collect policies, inventories, data flows, controls, evidence, incidents, findings and stakeholder input.
03
Assess
Evaluate classification, ownership, control coverage, exceptions, evidence and operating gaps.
04
Design
Define target principles, control domains, roles, policy architecture and evidence requirements.
05
Prioritise
Rank gaps and initiatives by risk, impact, readiness, dependencies and required decisions.
06
Mobilise
Validate the roadmap, owners, implementation patterns, governance cadence and handover plan.
Good fit when you need
- A common data security framework across business units, domains or platforms.
- Clear links between data classification, ownership and technical controls.
- A response to audit, customer, risk or regulatory concerns that cross several control areas.
- Security governance for a cloud, data-platform, AI, merger or modernisation programme.
- A risk-ranked roadmap before investing in new tooling or broad remediation.
- More traceable evidence, exception management and control reporting.
Not automatically included
- Penetration testing, red-team testing, vulnerability scanning or forensic investigation.
- Formal ISO certification, statutory audit, legal opinion or regulatory representation.
- Twenty-four-hour SOC monitoring or managed incident response unless separately commissioned.
- Software licensing, cloud consumption, security-product procurement or third-party audit fees.
- Production configuration changes without agreed access, change authority and acceptance criteria.
- A guarantee of compliance, certification, security or prevention of future incidents.
Get a Framework Scope, Deliverable Set and Commercial View
Share the control problems, platforms, data domains, obligations, findings or transformation initiatives that should shape the engagement. We will use them to define a practical scope before pricing.
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Custom Scope and Pricing for Data Security Framework Consulting
DataConsultant does not publish a fixed price for this service. A written commercial proposal is prepared after the framework boundary, evidence, stakeholders, required outputs and implementation depth are understood.
Commercial approach
Request a Quote
No approved fixed DataConsultant fee was available for this service. Current public Indian pricing for narrower ISO 27001 consulting and certification-readiness work varies materially by organisation size, scope and included audit support, so those benchmarks are not treated as an equivalent Data Security Framework price.
Request a Framework QuoteWhat shapes the commercial scope
Framework boundaryBusiness units, domains, jurisdictions, systems, environments and third parties.
Assessment depthEvidence review, interviews, workshops, control testing interfaces and documentation quality.
Control coverageClassification, access, encryption, sharing, DLP, monitoring, resilience and other agreed domains.
Technology complexityClouds, data platforms, IAM/PAM, security tools, legacy estates and integration dependencies.
Regulatory contextApplicable obligations, customer commitments, assurance needs and specialist-review interfaces.
Stakeholder modelNumber of owners, functions, forums, review cycles, workshops and decision gates.
Deliverable depthFramework, policies, control catalogue, RACI, evidence model, roadmap and implementation specifications.
Implementation supportMobilisation, remediation coordination, platform guidance, training, assurance or managed support.
Platform licences, cloud consumption, certification-body fees, specialist legal services, penetration testing, travel and third-party products are not assumed to be included unless explicitly stated in the approved commercial proposal.
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Why Consider DataConsultant for Data Security Framework Design
The service combines data governance, enterprise data architecture, security-control thinking and implementation planning without claiming unsupported certifications, proprietary products or guaranteed outcomes.
Protection requirements are connected to data ownership, classification, flows, platforms, quality, privacy and business purpose.
Control requirements can be designed around the organisation’s risks and target outcomes before selecting or changing technology.
Confirmed facts, assumptions, evidence gaps, exceptions, dependencies and decisions are made visible rather than hidden.
The framework is designed to lead into prioritised control mobilisation, operating routines, ownership and measurable improvement.
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Data Security Framework Questions for Buyers and Control Owners
Use these answers to evaluate fit, scope, delivery, standards, technology, regulatory considerations, commercial treatment and next steps.
What is a data security framework?
A data security framework is a structured management model for deciding how data should be classified, protected, accessed, shared, monitored, retained, recovered and governed. It connects business risk, data sensitivity, accountable owners, policies, control requirements, technology patterns, evidence and performance measures so security decisions can be applied consistently across the data lifecycle.
What is included in DataConsultant’s Data Security Framework service?
Scope can include stakeholder discovery, data and risk context, current-state control assessment, classification and handling requirements, ownership and decision rights, control principles, access and privileged-control requirements, encryption and key-management governance, secure sharing and third-party controls, monitoring and evidence design, incident and resilience interfaces, policy and exception workflows, KPI definitions and a prioritised implementation roadmap. Final scope is agreed during discovery.
How is a data security framework different from a cybersecurity framework?
A cybersecurity framework addresses cybersecurity risk at organisational level. A data security framework narrows that lens to how data is governed and protected across business processes, platforms and the data lifecycle. It can use broader references such as NIST CSF 2.0 or ISO/IEC 27001:2022 while adding data-specific decisions for classification, ownership, access, masking, encryption, sharing, lineage, retention, evidence and stewardship.
Who should sponsor a Data Security Framework engagement?
Sponsorship commonly sits with a CISO, chief data officer, CIO, CTO, risk or transformation leader, depending on the organisation. Effective design usually requires participation from data owners, security, privacy, legal or compliance, enterprise architecture, platform teams, identity and access management, risk, audit, business-domain leaders and operational teams.
When does an organisation need a data security framework?
Common triggers include inconsistent classification, uncontrolled data sharing, unclear access ownership, repeated audit findings, cloud or data-platform transformation, sensitive-data growth, AI adoption, third-party exposure, fragmented security tooling, regulatory change, merger or consolidation activity, and the need to prove that controls are operating across several business units or platforms.
What deliverables can we expect?
Typical outputs can include a current-state assessment, data security principles, target framework, control-domain model, classification and handling model, control catalogue, policy and standards architecture, role and decision-rights matrix, exception process, evidence and monitoring model, technology requirements, risk-ranked backlog, KPI framework, implementation roadmap and executive decision pack.
Can the framework be mapped to ISO/IEC 27001 or NIST CSF 2.0?
Yes, where relevant. DataConsultant can map framework requirements to recognised references such as ISO/IEC 27001:2022 and NIST Cybersecurity Framework 2.0 to support consistency, risk communication and control traceability. Mapping does not itself provide certification, legal compliance or an independent audit opinion.
Can the service support DPDP Act or CERT-In readiness in India?
The engagement can identify data-security requirements and evidence interfaces that may support readiness for applicable Indian obligations, including the Digital Personal Data Protection Act 2023, the Digital Personal Data Protection Rules 2025 and CERT-In directions. Applicability, commencement, legal interpretation and regulated conclusions must be validated by appropriately authorised legal, privacy, security, compliance or audit specialists.
Which technologies and platforms can be considered?
The framework can consider identity and access management, privileged-access tooling, cloud platforms, databases, warehouses, lakehouses, data catalogues, key-management and encryption services, data loss prevention, masking and tokenisation, security monitoring, logging, backup and recovery, ticketing, risk systems and evidence repositories. Recommendations remain requirements-led and vendor-neutral unless product selection or implementation is explicitly included.
How long does a Data Security Framework engagement take?
A reliable duration is confirmed after scoping. Timing depends on business units, jurisdictions, data domains, stakeholder availability, evidence quality, platform complexity, regulatory requirements, review cycles, the number of control areas in scope and whether implementation support is included.
How is Data Security Framework pricing calculated?
DataConsultant does not publish a fixed fee for this service. Pricing is scope-led and confirmed through a Request a Quote process after the required decisions, stakeholders, domains, control coverage, evidence depth, technology complexity, workshops, regulatory interfaces, deliverables, onsite needs and implementation support are understood.
Can DataConsultant help implement the framework?
Yes. Implementation support can be scoped separately or as a continuation of the design engagement. It can include control mobilisation, policy rollout, ownership and RACI activation, workflow design, platform requirements, evidence and KPI setup, prioritised remediation coordination, governance forums, training, implementation assurance and managed governance support.
What information should we prepare before the engagement?
Useful inputs include security and data policies, data classifications, system and platform inventories, architecture and data-flow diagrams, risk registers, audit findings, incident themes, access models, vendor information, retention requirements, security tooling, regulatory obligations, cloud standards, existing control catalogues and access to accountable business and technical stakeholders. Missing evidence is recorded as a limitation rather than assumed.
Does a Data Security Framework guarantee compliance or prevent breaches?
No. A framework can improve consistency, ownership, traceability and control readiness, but it cannot guarantee regulatory compliance, certification, security, audit acceptance or the absence of incidents. Legal opinions, certification audits, penetration testing, forensic work and regulated assurance require separately authorised specialist services where applicable.
Request a Data Security Framework Consultation
Complete the form with your current requirement. The enquiry will be sent to DataConsultant at support@dataconsultant.in.
Do not include passwords, secrets, production credentials or unnecessary sensitive data in the enquiry. Detailed technical evidence can be exchanged later through an agreed secure method if required.