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Business Intelligence (BI) Channel

Business intelligence (BI) has been referred to as the process of making better decisions through the use of people, processes, data and related tools and methodologies. The roots of business intelligence are found in relational databases, data warehouses and data marts that help organize historical information in the hands of business analysts to generate reporting that informs executives and senior departmental managers of strategic and tactical trends and opportunities. In recent years, business intelligence has also come to rely on near real-time operational data found in systems including enterprise resource planning (ERP), customer relationship management (CRM), supply chain, marketing and other databases. “Operational” BI is meant to provision many more functions in the organization with role-specific dashboards and scorecards and is increasingly tied to the topics of performance management and business process management. Inherent to any form of BI is the notion of data quality, consistent and dependable data and the processes involved in its creation and maintenance.

Articles

Analytics for Anyone

Role-based BI applications bring the value of analytics into the context of someone’s job

Case Study: Longbow Analyzes Candy Catalog’s Sweet Spot

Harbor Sweets transforms catalog campaign dynamics and sheds light on which campaigns are most beneficial

Role-Based Business Intelligence

Three critical success factors of role-based BI are focus, alignment and accountability

Handled With Care

Pitt Ohio Express tackles data quality without compromising flexible customer service.

BI Application Convergence: Build, Buy or Both?

As business intelligence evolves, prebuilt and custom-developed applications are converging.

Columns

Getting Started on Your Enterprise Business Intelligence and Data Warehousing Journey

Here are a few more things to consider before getting started or going too far down the path of developing an enterprise business intelligence and data warehouse capability.

Improving Business Intelligence: The Power of Metrics

Metrics are important to create an effective and successful program for improving BI quality.

A Scoring and Choice Model for Multistage Cross-Selling in the Insurance Industry, Part 1

In this column, I introduce a chain of data mining and predictive modeling techniques to identify the probable shopping patterns of customers buying related insurance products.

Emerging Trends in the World of Business Intelligence, Part 2

Part 2 continues to address trends within BI and data management by exploring the convergence of unstructured data and BI. This column also discusses data integration and data governance concepts.

Epidemiology and BI: Help for Designing Effective Intelligence

Sitting at the summit of the evidence hierarchy, companies who routinely use randomized experiments to develop and test their BI strategies can enjoy confidence in their findings.

Ask the Experts

Where is the best place for a BI application to reside?

Should the metadata layer that sits between the data marts and the query/reporting tools be owned by the business or IT?

Is there a good book for BI project management that you would recommend?

Where do I start with the charter to create a BI team, and will this work since the warehouse and other BI tools (such as ETL) are on a different team?

How do you decide on the roles and responsibilities of operational or analytical reporting teams?

White Papers

HP ERP Business Intelligence

By Hewlett-Packard

Business Intelligence for Tax Planning: Value, Strategy, and Vision

By Alan Y.C. Yong

Single Sign-On for Webintelligence

By Wipro Technologies

A Structured Method for Specifying Business Intelligence Reporting Systems

By BI Pathfinder Pty Ltd

Business Intelligence in a Real-Time World

By Netezza

Books

	Business Intelligence: The IBM Solution: Data Warehousing and OLAP By Mark Whitehorn, Mary Whitehorn
	Data Warehouse Design Solutions By Christopher Adamson (Editor), Michael Venerable
	Building the Operational Data Store, 2nd Edition By W. H. Inmon