Center For Business Intelligence

What is a Center for business intelligence excellence (COE)?

Many organizations have large IT shops involved with legacy system development and  maintenance based on traditional software development methodologies.

As they move towards an information management discipline and better use of business intelligence, they sometimes establish small centers of excellence to establish standards and best practices and to ensure that these they are adopted by the rest of the organization.

These centers of excellence include skilled center of business intelligence specialists with extensive experience in the areas of:

• Data modeling
• Database administration;
• Data integration;
• Data access;
• Business intelligence reporting and decision making;
  
• Metadata;
• Data quality; and
• Business intelligence project management.

What is a structure and design center for business intelligence?

The structure and design discipline focuses primarily on data modeling.

The goal is to provide direction on standards, best practices, and the use of conceptual, logical, and physical models, naming standards, and tools.

Data modelers in this discipline will require experience with data warehouse design and data mart design.

Business intelligence resources in this COE require extensive experience defining data requirements for analytic reporting and defining dimensional data modeling solutions.

What is a data storage center of excellence?

The data storage discipline focuses on the management of persistent data stores throughout the organization.  It covers such topics as database selection guidelines, backup & recovery procedures, data retention/archiving policies, and disaster recovery planning.

Database administrators in this discipline require extensive experience working in a data warehousing/business intelligence environment.

They are also usually heavily involved with integration testing and with test data acquisition.

What is a data integration center of excellence?

The data movement discipline focuses on the movement of data between systems.  In this context, “systems” include external data sources, operational systems, and analytic data stores.  Data movement encompasses the extract-transform-load (ETL) facilities used for bulk  data movement.  It also includes mechanisms to support continuous movement of discrete records, rows, or messages between systems.

Data integration requires developers experienced with extract, transform and load (ET) and data movement software development lifecycle.

They may be involved with extracting data from source systems and moving it to data warehouse structures and with extracting data from data warehouse structures and moving it to data mart structures.

What is a data access center of excellence?

The data access discipline is concerned with the means of delivering data from data stores to the consumers of the data.  In this context, “consumers” will be the business logic layer in an operational (not analytical) environment.  It includes standards for database drivers and protocols.

A major concern of the data access discipline is ensuring the proper separation between data access logic and business logic.  This aspect of data access is often considered within the scope of software architecture rather than data architecture. 

Specialists working in this discipline frequently provide technical support to other IT sectors  in addition to the business intelligence COE's

What is a data usage center for business intelligence excellence?

The data usage discipline is concerned with the tools and techniques used to enable data analysis by end-users.  In this context, data analysis includes:

• End-user customizable reports;
• Online analytic processing (OLAP); and
  
• Data mining.

What is a metadata management center of excellence?

Metadata is data describing or specifying other data or defining and organizing characteristics that need to be known about data, including (but not limited to) information about physical data representations, technical and business processes, rules and constraints, and data structures. 

Business intelligence resources involved with metadata management practices enable information used by management in its daily decision-making and in its long-term strategic planning to be accurate, accessible, complete, consistent, timely, valid and relevant and assists in maintaining high integrity over production data.

What is a data quality center of excellence?

Data quality is not a stand-alone discipline.  Rather, data quality is a result of adherence to a sound data management methodology. 

Business intelligence resources involved in this disciple require experience with:

• Data validations in operational legacy 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 (both technical and business) across systems including the ETL environment

• Tasks and Deliverables;
• Guidelines and Best Practices;
• Roles & Responsibilities; and
• Work Breakdown Structure.

• Structure and design
• Data storage
• Data integration
• Data access
• Data Usage;
• Metadata management;
• Data quality; and
• Business intelligence management practice.