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Business Intelligence Best Practices

Improve effectiveness with David Bowman’s information management guidelines for business intelligence best practices

This site is designed for Information Technology professionals who need to improve effectiveness and require guidance and direction to help teams consistently produce error free results.

It provides information management guidelines for business intelligence roles and responsibilities and best practices.

What is Business Intelligence
?
  • Should focus on the tools and techniques used to enable data analysis by end-users; and
  • 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
Roles and Responsibilities

Solution Architect
  • Should have overall responsibility for the entire data warehouse solution;
  • Should provide technical/management direction to the data warehouse team to ensure the integrity of the data warehouse; and
  • Should have overall responsibility for the quality of all data architecture deliverables.
Business Intelligence Architect
  • Should have overall responsibility for the business intelligence  solution and all deliverables;
  • Should define business intelligence reporting and analytic requirements as part of requirements specification;
  • Should provide technical direction to assigned business intelligence developers; and
  • Should be responsible to the solution architect for the quality of all business intelligence deliverables.
Business Intelligence Developer
  • Should be accountable to the Business Intelligence Architect for the detailed design and development of business intelligence reporting and analytics components;
  • Should create unit test plans;
  • Should develop business intelligence code;
  • Should perform unit testing;
  • Should document unit test results;
  • Should compile business intelligence object migration inventory; and
  • Should respond to defects identified during testing.
Business intelligence Infrastructure
  • Should support business intelligence solution design;
  • Should support business analytic requirements;
  • Should support business intelligence reporting;
  • Should support decision support requirements;
  • Should provide knowledge workers the capability of direct access to detailed data using a standardized tool suite;
  • Should not require intervention by Information Technology professionals;
  • Should provide a semantic metadata layer to allow end users to have a business view of the data which is translated for access into the underlying physical database structure by the tool;
  • Should consider allowing power users direct access to data using more advanced tools;
  • Should implement security through a combination of data and application level access controls.
  • Should consider common business intelligence tools such as Business Objects, from SAP, Cognos, from IBM, Enterprise Guide, from SAS, MicroStrategy, Oracle Business Intelligence Enterprise Edition, from Oracle, SQL Server Analysis Services, from Microsoft, and WebFocus, from IBM;
  • Should consider common data visualization and discovery tools such as Visual Analytics, from SAS, Domo, QlikView, from QlikTech, Spotfire, from TIBCO and Tableau; and
  • Should consider common data mining tools such as Enterprise Miner, from SAS, KXEN, from SAP and SPSS, from IBM.
Business Intelligence
  • Should maintain a history of changes and support slowly changing dimensions;
  • Should provide a semantics layer, shielding business users from having to understand technology and IT-related terms;
  • Should include usage-monitoring reports;
  • Should be capable of logging usage data;
  • Should identify data elements in demand versus those that have become obsolete and can be removed;
  • Should proactively manage performance impact through usage governors;
  • Should provide a full range of Business Intelligence capabilities e.g. operational reporting, ad-hoc query reporting, OLAP, data mining, corporate intranet portals, corporate performance management scorecards, dashboards, etc;
  • Should include analytic applications;
  • Should define a data classification scheme, which identifies different levels of data sensitivity and the corresponding protective measures; and
  • Should provide the capability, where appropriate, for business user to “drill through” or “drill across” the various physical and logical layers in the information.
Summary...

Information delivery should focus on the tools and techniques used to enable data analysis by end-users; and 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.

This site provided information management guidelines for business intelligence roles and responsibilities and best practices.