The document discusses the interactions between data security and data quality. It argues that poor data quality can threaten data security by compromising confidentiality, integrity and availability. Improving data quality through processes like data governance can benefit data security by providing metrics to evaluate effectiveness and enabling security requirements to be implemented properly. The document then presents models for data quality and data security and argues that integrating the two through a unified data governance strategy can help discover vulnerabilities, engineer better security protections and create organizational awareness of both data quality and security issues.

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

5. Data Accountability

7. Data Encryption

9. Data Loss Prevention

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

16. Remove Silos

17. Definition

18. Domain

19. Purpose

20. Data Governance policies

21. Quality Audits

22. Quality Reports

23. Executive support

24. Manage data as a quality asset

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

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

40. Modification rules

41. Access rules

42. Access points

44. Effectiveness of SAR and SFREverybody 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