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Data Quality+Security

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A short summary of the interactions between Data Quality and Data Security. …

A short summary of the interactions between Data Quality and Data Security.

See my other presentations on the topic for more details.

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  • 1. Interactions between Data Securityand Data Quality
  • 2. Data Quality and Data Security
    Models
    Data Governance integrating
    Data Quality and Data Security
    Agenda
    Data Quality Maturity Model and
    Data Security
  • 3. Data Quality Issues are a Security Threat
    Confidentiality, Integrity and Availability Problems as a result of Poor Data Quality
    Data Ownership is required to control whether confidentiality is maintained.
    Data Inconsistency measures are required to control if integrity is maintained.
    Analysis of Data problems hands confidential data to people that shouldn’t have!
    “ad hoc” Fixing Data problems is in itself a big threat to data integrity!
    Data Quality Benefitting Data Security in all Stages
    Qualitative Data Governance provides metrics to observe the effectiveness of Data Security.
    Data Quality processes are required to effectively implement Data Security Requirements.
    Data Quality Enables Data Security
  • 4. The Data Security Model
    Integrity
    • Modification Tracking
    • 5. Data Accountability
    • 6. Data Authenticity
    Confidentiality
    • Data Access Controls
    • 7. Data Encryption
    • 8. Data Anonymization
    Availability
    • Data Access Mechanisms
    • 9. Data Loss Prevention
    • 10. Downtime Prevention
  • The Data Quality Model
    Do the IT systems provide
    high quality data for
    their purpose?
    Do the processes
    provide data suitable
    to fit their purpose?
    Fit For
    Purpose
    Measure
    Analyze
    Improve
    Control
    Measure
    Analyze
    Improve
    Control
    Data
    Quality
    Mgt.
    Which processes
    utilize the data
    and why?
    Why do the IT systems
    handle the data?
    Data Handling
    IT Systems
    Data Utilizing
    Processes
    Measure
    Analyze
    Improve
    Control
    Do the systems provide
    data suitable to
    the process?
    What data handling function
    does the system provide
    for the process?
  • 11. Data Quality Characteristics
    The Data Quality Characteristics
    Consistent
    Complete
    Transparent
    Relevant
    Timely
    Precise
    Accurate
  • 12. The effect of Data Quality on Security
    Poor
    Data
    Quality
    Data
    Security
    Threats
    Fixing
    DQ
    Problems
    Data
    Security
    Metrics
    causes
    improves
    Timeliness
    Transparency
    Consistency
    Completeness
    Relevance
    Precision
    Accuracy
  • 13. Data Quality and Data Security
    Models
    Data Governance integrating
    Data Quality and Data Security
    Agenda
    Data Quality Maturity Model and
    Data Security
  • 14. The Data Quality Maturity Model
    Enforcement
    Metadata
    Methods
    Policy
    Metadata
    Management
    Information Lifecycle Mgt.
    Data Risk Management
    Data
    Architecture
    Data
    Quality
    Governance
    Maturity
    Organizational
    Awareness
    Value Creation
    Audits &
    Reporting
    Stewardship
    Security
    Compliance
    Data Quality
    Measurement
    Corporate
    Environment
    Man
    DQ
    Control
  • 15. DQ Governance Benefits for Security
    Enforcement
    Metadata
    Methods
    Corporate
    Environment
    Man
    DQ
    Control
    Organizational
    Awareness
    Policy
    Value Creation
    Metadata
    Management
    Information Lifecycle Mgt.
    Audits &
    Reporting
    DQ Perspective
    Stewardship
    Data Risk Management
    Security
    Compliance
    Data
    Architecture
    Data Quality
    Measurement
    • Address data quality in design
    • 26. Points of Data Entry, Utilization and Decommission
    • 27. Inconsistency:Count, Cause, System, Solution
    • 28. People in charge
    • 29. Common skill set for data issues
    • 30. Integrated business processes
    • 31. Rational standards
    Organizational
    Awareness
    Policy
    Value Creation
    Metadata
    Management
    Information Lifecycle Mgt.
    Audits &
    Reporting
    • Discover soft spots
    • 32. Engineer security
    • 33. Assigned Responsibilities
    • 34. Security Levels
    • 35. Security policies
    • 36. Security Audits
    • 37. Security Reports
    • 38. Manage data as a valuable asset
    • 39. Effective protection for valuable assets
    DS Perspective
    Stewardship
    Data Risk Management
    Security
    Compliance
    Data
    Architecture
    Data Quality
    Measurement
    • Address data security in design
    • 40. Modification rules
    • 41. Access rules
    • 42. Access points
    • 43. Integrity threats:
    Amount, Location, Countermeasures
    • Single Point of enforcement
    • 44. Effectiveness of SAR and SFR
    Everybody wins – why not build a synergetic strategy?
  • 45. Data Quality and Data Security
    Models
    Data Governance integrating
    Data Quality and Data Security
    Agenda
    Data Quality Maturity Model and
    Data Security
  • 46. Roadmap to Integrated DQ/DS Governance
    Recognizing data as a corporate asset:
    Processes, owners, KPI’s + improvement.
    Documentation,
    Standardization &
    Application of
    Service Processes.
    Service
    Management
    Data
    Management
    Integrated Data Governance
    Data
    Administration
    Problem
    Management
    Error removal capabilities:
    Staff, tools, method.
    Information Model, Documentation, Standardization and Monitoring of Data.
  • 47. Service Management
    Data Quality Focus in Service Management
    Integrate Data Services into Service Management Processes
    Data-driven SLA’s
    Service
    Management
    Data
    Management
    Innovation and technology change based on data capability
    Integrated Data Governance
    Benefits for Data Security Management
    All relevant data objects become visible on the radar
    Data
    Adminsitration
    Problem
    Management
    Gaps in data services become obvious
    Plan security into the design concepts before realization
    Corporate learning allows security “best practices” to spread quicker
    Data Service Management is the basis for DS to effectively handle + implement security.
  • 48. Problem Management
    Data Quality Focus in Problem Management
    Establish a common body of knowledge and tools for solving data issues
    Establish a central problem management team to tackle data issues
    Service
    Management
    Data
    Management
    Enterprise-wide scope for data problem handling
    Integrated Data Governance
    Benefits for Data Security Management
    Central unit to track SAR and SFR problems
    Data
    Administration
    Problem
    Management
    Synergies in resolving security issues caused by quality issues
    Joint priorities on interdisciplinary issues
    Effective handling of corporate issues that only slightly relate to data
    Data Problem Management is the basis for DS to get rid of security problems at the root.
  • 49. Data Administration
    Data Quality Focus in Data Administration
    Common Data Models
    Metadata standards
    Service
    Management
    Data
    Management
    Central control and clearly defined data accountability
    Integrated Data Governance
    Benefits for Data Security Management
    Standard method for integrating SAR into metadata
    Data
    Administration
    Problem
    Management
    Standard processes for turning SFR into action
    Standard metrics for tracking SFR implementation
    SAR realization as “everyone’s” accountability
    Data Administration is the basis for DS to touch data threats at the right place.
  • 50. Data Management
    Data Quality Focus in Data Management
    Establish rules and procedures for data management
    Treat data as a corporate asset
    Service
    Management
    Data
    Management
    Track and improve data KPI’s
    Integrated Data Governance
    Benefits for Data Security Management
    Integrate SARs as standard KPI
    Data
    Administration
    Problem
    Management
    Measurement tools discover integrity violations
    Common knowledge on data-related issues and threats
    Corporately aligned strategy for implementing data controls
    Data Management offers DS the certainty that counters are properly implemented.
  • 51. Thank you for your attention

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