Business Intelligence systems allow organizations to improve business performance by leveraging information about customers, suppliers, and internal business operations. BI systems:

• Extract data from many sources, such as Customer Relationship Management (CRM), Supply Chain Management (SCM), and Enterprise Resource Planning (ERP) systems, and other applications.
• Centralize, organize, and standardize information in repositories, such as data warehouses and data marts. This may also involve cleaning the data and appending additional data.
• Provide analytical tools that allow a broad range of business and technical specialists to run queries against the data to uncover patterns and diagnose problems.

Extract, Transform and Load (ETL)

Data integration technology is generally used to extract transactional data from internal and external source applications to build the data warehouse. This overall process and the steps in it are referred to as ETL for extract, transform and load. The data is extracted from its source application or repository, transformed to the format needed for the data warehouse, and then loaded into the data warehouse. Data integration technology works hand-in-hand with technologies like Enterprise Information Integration (EII), database replication, Web Services, and Enterprise Application Integration (EAI) to bridge proprietary and incompatible data formats and application protocols.

Data Warehouses and Data Marts

A data warehouse or data mart stores tactical or historical information in a relational database and allows the user to extract and assemble specific data elements from a complete dataset to perform a variety of analyses. The data warehouse can be architected according to schema (star, snowflake, etc), data composition (values and attributes) and dimension levels, and descriptors. Data marts enable additional segmentation within a broader data warehouse environment.

Query, Reporting and Analysis

Technical and business analysts use a variety of tools to access data, analyze information, and view the results. They include:

• Query and Reporting Tools Most BI systems allow users to perform historical, "slice-and-dice" analysis against information stored in a relational database. This type of analysis answers "what?" and "when?" inquiries. A typical query might be, "What was the total revenue for the eastern region in the third quarter?" Often, users take advantage of pre-built queries and reports.
• On-Line Analytical Processing (OLAP) and Data Mining. OLAP analytical engines and data mining tools allow users to perform predictive, multidimensional analysis, also known as "drill-down" analysis. These tools can be used for forecasting, customer profiling, trend analysis and even fraud detection. They answer "what if" and "why?" questions, such as, "What would be the effect on the eastern region of a 15 percent increase in the price of the product?"
  
• Business Performance Management. BPM uses real-time business intelligence to proactively improve productivity and encourage continuous process improvement in an enterprise. This approach extends the more traditional approach of business scorecards and can include financial, organizational, customer service, supply chain, and channel performance management.
• Information Delivery. Query results and reports can be delivered through dedicated desktop applications, dashboards, intranets, and extranet portals.

Business Intelligence and Web Services

Business Intelligence is being fundamentally changed by eXtensible Markup Language (XML) and the emerging Web Services model. XML provides a universal syntax for the representation of data, enabling integration and analysis across BI environments and across traditional organizational and technical boundaries. As this area evolves, it becomes easier for different organizations to share data.

For more information on choosing the right BI solution for your company, please read our Business Intelligence First Steps.

Go to Bitpipe Research Guide: Business Intelligence.