The document discusses six governance processes for data and business intelligence: data lifecycle, data models, data quality, data security, data warehousing, and metadata. For each process, it provides an overview of why governance is important in that area, and what the governance process will do to manage issues and ensure requirements are met. The governance processes aim to balance various factors, control changes, and provide oversight and accountability for data management.

1. DATA WAREHOUSING & BUSINESS INTELLIGENCE
GOVERNANCE PROCESS
WHAT WE CAN YOU FOR YOUR BUSINESS
DATA MANAGEMENT &
WAREHOUSING

2. WHAT WE OFFER:
• Six governance processes that cover
the entire BI & DW Lifecycle
– Data Lifecycle
– Data Models
– Data Quality
– Data Security
– Data Warehousing
– Metadata
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3. OUR GOVERNANCE PROCESS TEMPLATE
• People
– Roles and Responsibilities
• Defined responsibilities
• Accountability
– Forums
• Purpose or each forum or communication tool
• Authority to make decisions
• Participants who should contribute
• Processes
– Methodologies
• Description of the process
• Links to and compliance with standard processes
• Use of standard documentation
– Standards
• Reference documents for the consistent use of IT
– Tools
• Tools to support projects
• Tools to support operational area
– Compliance
• Collection and analysis of metrics
• Audits of projects
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4. WHAT WE DELIVER:
THE PROCESS DOCUMENTATION
• A Governance Framework Presentation
used for briefing and training
• Detailed “Wallchart” Process Diagrams
that have been expanded to give greater
clarity and aid in understanding the
process.
• The Governance Process Manual – a
detailed document that covers the entire
process
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5. GOVERNANCE PROCESS:
DATA LIFECYCLE
• The Data Lifecycle describes how the data stored in the Data Warehouse is
managed over time.
• Conflicting factors need to be balanced:
– Capacity
• Capacity is finite, and extension has a cost associated.
– Performance
• Performance is affected by data volume and hardware.
– Historical Reporting
• Users require historical information for reporting.
– Regulation
• Regulation of what data can be retained and for how long.
– Archive, Backup and Restoration
• Has performance, capacity and cost implications, and will also be regulated.
• Data Security Governance will:
– Put in place a process for managing, and balancing these factors.
– Allow Business users to understand and request changes to the Data Lifecycle
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6. GOVERNANCE PROCESS:
DATA MODEL
• Governance of the Data Model is important to organisations because:
– The Data Model is the basis for controlling all data flow into and out of the Data
Warehouse, ensuring that performance is optimised and that the Query
Requirements of the user are fulfilled.
– Failure to create and maintain a robust Data Model can result in:
• Poor Load performance
• Poor Query Performance
• Inconsistency in Warehouse output and misinterpretation of results
• Higher cost of Maintenance
• Poor Data Quality
• Data Model Governance will:
– Put in place a process for controlling changes to the Data Model and ensuring
consistency.
– Help facilitate performance gains for the User’s Queries, and in the loading of
Data from the Source Systems through to the Data Marts
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7. GOVERNANCE PROCESS:
DATA QUALITY
• Data Quality is important to organisations because:
– They rely on data for decision making will need to be certain that the information
being used is correct.
– Failure to ensure this data is accurate, complete and available in time can result
in:
• Missed Business Opportunities
• Poor Strategy Decisions
• Loss of Market Position
• Poor understanding of the Business Operations
• Diminished Customer Relations
• Unnecessary Expenditure
• Data Quality Governance will:
– Put in place a process for identifying and resolving problems with business data.
– Provide the controls and measures for understanding the quality of the data and
allow for the Business Users to be confident in their decision making.
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8. GOVERNANCE PROCESS:
DATA SECURITY
• Data Security describes who can access what data, when and where.
• Conflicting factors need to be balanced:
– Architecture
• Architecture can enable the Security Model to be simplified by separating data with different Security requirements.
– Data Lifecycle
• Security implementations will have to apply to live data as well as archived data.
– Business Unit Requirement
• Business Units will have different requirements over who can access data. Eg. Argus
– Compliance
• Legislation such as Data protection will stipulate security on some data types. Eg. Customer Data.
– Company Policy
• Protection for certain sensitive company data. Eg. HR Data or Performance Data.
– Business Intelligence Personnel
• Special access levels for certain Data Warehouse Personnel. Eg. Data Quality Analyst
– Business Intelligence Mission
• To freely provide information to those that need it. Approved at a high level.
• Data Security Governance will:
– Put in place a process for managing, and balancing these factors.
– Allow Business users to understand and request changes to Data Security
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9. GOVERNANCE PROCESS:
DATA WAREHOUSING
• Data Warehousing Governance is important because:
– Data Warehousing projects are large, time-consuming and expensive
– Users are often disappointed with the accuracy and performance of data
warehouses
– Often large sections of data warehouses are unused
– Load times often extend beyond the time allocated
• Data Warehousing Governance will ensure that:
– The user requirements will be met effectively
– The scope will be limited to user requirements which deliver benefit at
agreed cost
– The project timescales will be predictable
– The solution will be robust and require limited re-work
– The data will be accurate and up-to-date
– The changes and issues will be handled promptly
– The performance of loading and querying will be adequate
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10. GOVERNANCE PROCESS:
METADATA
• Business Metadata
– Definitions - Business Terms, Acronyms and Abbreviations, also the business description for Data Elements
– Ownership - Of the data, the definitions, the responsibility for maintenance
– Relationships - how definitions, data sources and ownerships overlap or relate to one another
• Technical Metadata
– Availability - expected availability of a system, such as the batch window, the Service Level Agreement (SLA), and
the query window for the users
– ETL - execution times of the various ETL elements, the individual and overall run times, counts of the records
inserted, updated and deleted, and information about when the ETL mappings were created or changed
– Querying - Queries being executed by the users, the execution time and duration, and the tables and fields being
accessed
– Data Rules - Details such as maximum string lengths, accepted values, and number precision
– Data Quality - Output from the Automated Data Checking System and the Issue Tracking System
• Metadata System - It is not expected that a single system can capture and store all of a company’s Metadata, but rather
that the Metadata solution is a collection of heterogeneous systems used together.
• Metadata Governance will:
– Put in place a process for creating new Business and Technical Metadata, controlling changes to the Metadata
and ensuring consistency of capture.
– Lead to better understanding of Business Definitions, Batch Window Utilisation, ETL Processing and Query
Performance.
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11. OUR GOAL
• To help you design, deliver,
implement and execute good
governance of
– Data Lifecycle
– Data Models
– Data Quality
– Data Security
– Data Warehousing
– Metadata
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12. CONTACT US
• Data Management & Warehousing
– Website: http://www.datamgmt.com
– Telephone: +44 (0) 118 321 5930
• David Walker
– E-Mail: davidw@datamgmt.com
– Telephone: +44 (0) 7990 594 372
– Skype: datamgmt
– White Papers:
http://scribd.com/davidmwalker
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13. ABOUT US
Data Management & Warehousing is a UK based
consultancy that has been delivering successful
business intelligence and data warehousing
solutions since 1995.
Our consultants have worked with major
corporations around the world including the US,
Europe, Africa and the Middle East.
We have worked in many industry sectors such as
telcos, manufacturing, retail, financial and
transport. We provide governance and project
management as well as expertise in the leading
technologies.
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14. DATA WAREHOUSING & BUSINESS INTELLIGENCE
GOVERNANCE PROCESS
THANK YOU
DATA MANAGEMENT &
WAREHOUSING