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LESSON - Data Warehouse Alternatives: Seven Data Integration Options for BI Solutions

By Kevin R. Quinn, Vice President of Product Marketing, Information Builders, Inc.

While data warehouses are important for many types of analytical systems, many BI applications are better served with data integration technologies that pull data into reports as needed. There are seven basic ways to integrate and access data to solve various business problems.

1. Traditional Data Warehouse

Data warehouses traditionally involve gathering data from multiple sources to create an aggregated source of information for reporting. Information is extracted from production data sources as it is generated (real-time information), or in periodic stages (latent information). It is often simpler and more efficient to run queries against this data, rather than to access each data source separately. Traditional data warehouses work well when you need to reduce overhead on a transaction-processing system, analyze historical data that is no longer accessible in operational applications, or aggregate data from multiple sources.

2. Real-Time Data Warehouse

Real-time data warehouses are constantly updated by “trickle-feeding” data from production data sources, rather than uploading data in batch mode at periodic intervals. This is a good approach when you need current data in your reports. Instead of migrating data from operational systems into a central data warehouse, you can use real-time integration technology to deliver the data whenever it is entered into operational systems.

3. Operational Data Access

Operational business intelligence systems give users a real-time view of business events as they occur, such as shipping orders to customers, routing parts through an assembly line, or sending trouble tickets to customer service reps. These applications generally obtain information from an automated workflow process or directly from production systems. There is less latency between when an event occurs and when the BI system is aware of that event, putting business users in touch with current information.

4. Enterprise Information Integration (EI )

Enterprise information integration (EII) refers to the real-time aggregation of data across multiple data sources. EII solutions present distributed data as if it exists in a single location. This distinguishes EII from other types of data access technologies, since data is not permanently moved or replicated into a new location or database. The source data remains intact.

5. Process Integration

Users querying a database or running a report typically initiate analytical BI systems. However, a BI system can also be triggered by a business process. For example, when an ERP system receives an order or a manufacturing process updates a bill of materials, these events might notify other applications. In some cases, users are asked to supply input. In other cases, there is no user input involved.

6. Search Technology

Most search engines are designed to index and track Web pages, not database transactions. However, with the right integration technology, you can use search technology to unleash information that is locked up in proprietary information systems as well. This enables users to search dynamic business intelligence content in addition to structured and unstructured data sources, and to create Google-style results from data sources throughout the enterprise.

7. Web Services

With the right Web services adapter, you can treat data coming from an Internet Web service as if it were stored in a relational table. This offers many reporting and analytical options—without recourse to a data warehouse. For example, a purchasing officer might need to review a supplier’s inventory, pricing, and delivery options to determine which items to restock. If that information is available as a Web service, the officer could retrieve it in a single report and make an instant re-stocking decision.


A complete integration platform can streamline all of these data integration projects by providing a cohesive solution for extract, transform, and load (ETL) procedures, EII initiatives, Web services deployments, and many types of business process integration scenarios. Analyze each business challenge to understand whether a data warehouse or another type of information-access method presents the best solution. Always try to identify the best method at the outset of the project, and don’t assume that a data warehouse is the correct solution before assessing all the options.

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