The main concepts of the governance for your data projects

1. ( Big ) Data Management
Governance
Global Concepts in 5 slides
2016
Nicolas SARRAMAGNA
https://fr.linkedin.com/pub/nicolas-sarramagna/19/941/587

2. CONTENTS
 Introduction
 What
 Why
 How
 References

3. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance in Data Management 3
 DATA MANAGEMENT
 Multiples modules
 BIG DATA
 Velocity, Volume, Variety, Veracity, Value
Collect
Storage
Data Mining /
Machine Learning
Data Viz
Governance
Security
Master Data
Data quality

4. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance – What 4
 GOVERNANCE IS
 Evaluate -> Lead -> Measure
 ACTIONS
 To define, approve, communicate, track and enforce conformance of data strategies, policies, standards,
architecture, procedures and metrics
 To sponsor, track and oversee the delivery of data project management projects and services
 To prevent, manage and resolve data related issues
 To understand and promote the value of data assets

5. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance – Why 5
 WHY
 To keep the services of the DMP under control (modules of collect, storage, data quality, ….)
 To increase consistency and confidence in decision making through accurate, accessible, and actionable data : IT
merge, time to market, competitiveness, to go on new sector
 To reduce data management issues about
 Discovery : find the right information
 Integration : manipulate and combine information
 Dissemination : consume information
 Insight : extract value and knowledge from information
 Management : manage and control information volumes and growth
 Security : in particular disponibility and audit

6. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance – How 6
 USAGES OF STANDARD
 COBIT 5
 DMBOK Planning, Development, Control, Operational Activities
 BUILD GOVERNANCE WITH
 Roles, Responsibilities -> RACI
 Policies
 Procedures
 Business Rules
 Data Usage
 Workflow
 Data Audits
 Measures / Metrics
 Reporting

7. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance – How 7
 START
 Determine enterprise data needs and data strategy
 Understand and assess current state data management maturity level
 Establish future state data management capability
 Establish data professional roles and organizations
 Develop and approve data policies, standards, and procedures
 Plan and sponsor data management projects and services
 Establish data asset value and associated costs
 RUN
 Coordinate data governance activities
 Manage and resolve data related issues
 Monitor and enforce conformance with data policies, standards, and architecture
 Communicate and promote the value of data assets
 EVALUATE MATURITY WITH METRICS
 Data value
 Data management cost
 Achievement of objectives
 Number of decisions made
 Steward representation and coverage
 Internal, external resources vs needs
 Data solution, services portfolio vs needs
 Data infrastructure vs needs
 Data management process maturity

8. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Governance - References 8
 REFERENCES
 http://www.isaca.org/chapters3/Atlanta/AboutOurChapter/Documents/GW2014/Implementing%20a%20Data%20G
overnance%20Program%20-%20Chalker%202014.pdf
 https://web.stanford.edu/dept/pres-provost/irds/dg/files/StanfordDataGovernanceMaturityModel.pdf
 http://fr.slideshare.net/alanmcsweeney/data-information-and-knowledge-management-framework-and-the-data-
management-book-of-knowledge-dmbok-3366885
 http://www.isaca.org/COBIT/Pages/COBIT-5-Framework-product-page.aspx
 Book : Multi-Domain Master Data Management: Advanced MDM and Data Governance in Practice