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Information Management Framework

Improve management process with David Bowman’s guidelines for Information Management Framework

This site is designed for Information Technology professionals and management consultants who need to improve process and productivity and want information management guidelines

It provides an enterprise information management framework and  introduces polices, standards and best practices required to govern accountability for the quality of information required for management and business intelligence purposes.

Enterprise Information Architecture
Enterprise Information Architecture

  • Should establish data warehouse principles
  • Should establish a framework to guide decision makers and clarify industry terminology
  • Should outline the structure of information management polices, standards and best practices.
  • Should provide direction for structure and design, data storage, data integration, information delivery, data security data quality and metadata
Data Architecture
  • Should focus primarily on data modeling and project deliverables that flow from data modeling activities.
  • Should provide direction on data architecture best practices including data model standards, modeling tools and the use of data model, conceptual data model, logical data model, relational data model and physical data model.
Database Management
  • Should focus on the management of persistent data stores.
  • Should provide direction on database management best practices, systems selection guidelines, backup and recovery procedures, data retention and archiving policies, disaster recovery planning and physical database architecture.
Data Integration
  • Should focus on the movement of data between systems.
  • Should provide direction on the extract transform load facilities used for bulk data movement including mechanisms to support continuous movement of discrete records, rows, or messages between systems including data integration best practices.
Information Delivery
  • Should focus on the tools and techniques used to enable data analysis by end-users. 
  • Should provide direction on business intelligence and analytics including business intelligence best practices, data analysis, end-user customizable reports, online analytic processing and data mining
  • Should provide a centralized function to administrator user ids, passwords, roles, etc.
  • Should ensure that LDAP (or an equivalent standard) is used to manage a centralized directory of security and authorization information
  • Should provide direction on data warehouse security.
Data Quality
  • Should be achieved by adherence to a sound data management methodology and data governance process.
  • Should include data quality standards to address data validations in operational systems; validation of purchased data sets; quality checks on data extracts; audit controls to verify integrity of bulk data movements; and use of common field validations across systems including the data integration environment
  • Should have touch points throughout each enterprise information management architecture discipline e.g. the data design discipline will populate the repository with entity and attribute definitions; technical metadata will include information about where (in which databases) specific tables are stored; analytic data access tools will make use of the business metadata to provide entity and attribute definitions to the end user; data integration  processes will access business metadata to retrieve validation and transformation rules to be applied during the data integration processes.
  • Should provide direction on metadata standards.

Information management is a discipline that governs accountability for the structure and design, storage, movement, security, quality, delivery and usage of information required for management and business intelligence purposes.

This site provided an enterprise information management framework and introduced polices, standards and best practices required to govern accountability for the quality of information required for management and business intelligence purposes.