Implementing BI & DW Governance


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Implementing BI & DW Governance

  2. 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 © 2012 Data Management & Warehousing 2
  3. 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 © 2012 Data Management & Warehousing 3
  4. 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 © 2012 Data Management & Warehousing 4
  5. 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 © 2012 Data Management & Warehousing 5
  6. 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 © 2012 Data Management & Warehousing 6
  7. 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. © 2012 Data Management & Warehousing 7
  8. 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 © 2012 Data Management & Warehousing 8
  9. 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 © 2012 Data Management & Warehousing 9
  10. 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. © 2012 Data Management & Warehousing 10
  11. 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 © 2012 Data Management & Warehousing 11
  12. 12. CONTACT US •  Data Management & Warehousing –  Website: –  Telephone: +44 (0) 118 321 5930 •  David Walker –  E-Mail: –  Telephone: +44 (0) 7990 594 372 –  Skype: datamgmt –  White Papers: © 2012 Data Management & Warehousing 12
  13. 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. © 2012 Data Management & Warehousing 13