What is a Data Warehouse?

A data warehouse, or in Dutch, a ‘gegevensmagazijn,’ is a crucial concept in the world of business intelligence. In this article, we will delve deeper into the meaning and role of data warehouses within Oracle Business Intelligence (BI) in conjunction with Oracle JD Edwards.

We will also discuss how data warehouses collect vast amounts of data from various source systems and make them available for quick and meaningful analyses in an efficient manner.

What is a data warehouse?

At first glance, a data warehouse may seem nothing more than a database, with tables, fields, and records of data.

However, what sets it apart is its ability to systematically collect vast amounts of data from diverse source systems.

This data is stored in what is known as ‘cubes,’ where different aggregation levels are maintained.

Moreover, a data warehouse has the capability to capture historical data over time, referred to as ‘Slowly Changing Dimensions’ in the Ralph Kimball method.

Why is Data Warehousing Important?

Consider a scenario where a new sales representative comes in to take over the responsibilities of someone who is retiring. If this representative is linked to the customers he is going to serve, we can gain immediate insight into his performance and revenue.

To keep this information accurate, it’s essential to understand how time plays a role and what statuses employees have, such as ‘In Service’ and ‘Out of Service.’

Another example is information about outstanding invoices. Oracle JD Edwards can provide information about outstanding invoices and their payment status at the moment. But if we want to compare historical data to analyze how customers behave, JD Edwards struggles to provide this information.

This is where a data warehouse comes in handy. It can handle all these aspects, offering the ability to centralize information from various sources and systems within the organization.

This means even outdated data structures, Excel spreadsheets, and text files can be integrated into a central database accessible to Oracle BI solutions.

As a result, we can easily combine and compare sales order history from Oracle JD Edwards with data from a CRM system, for example, to analyze order success and the duration of quotes.

Transactional Database vs. Data Warehouse Database

When installing an Oracle Database, the choice between a transactional database and a data warehouse database is crucial.

This choice impacts the database configuration, as SQL queries for transactional databases and data warehouses are optimized differently.

Storing transactional data is fundamentally different from analyzing historical data in a data warehouse.

Data Warehousing in the World of Oracle JD Edwards and Oracle BI

Within Oracle JD Edwards and Oracle BI, there is no strict necessity for a data warehouse if the data volume is limited.

In this case, Oracle BI can directly query the Oracle JD Edwards database. This is especially useful for organizations with smaller data volumes.

Key Considerations in Oracle BI Implementation

When considering Oracle BI implementation, there are some crucial considerations:

1. How can heavy SQL queries on the operational Oracle JD Edwards system be avoided?
2. What are the requirements for historical data and ‘Slowly Changing Dimensions’?
3. What are the performance requirements?
4. Which combinations of data from other systems are needed in the Oracle BI solution?
5. How current should the data be?

Alternatives to Data Warehousing

Implementing a data warehouse brings additional complexity, management, and costs. Not every organization is immediately willing or able to take on this challenge.

Fortunately, there are alternatives, ranging from staging areas and data replication to simplified solutions like materialized views in the Oracle JD Edwards database.

These alternatives can serve as a kind of ‘Data Warehouse Light.’

Oracle BI Applications

For organizations using Oracle JD Edwards, Oracle BI Applications provide ready-made dashboards, analytics, and data access for areas such as finance and sales order management.

These solutions also include a pre-configured data warehouse. Additional modules can be added as needed.

Conclusion

A data warehouse is a powerful tool to integrate data from diverse sources and enable meaningful analyses.

The decision to implement or not implement a data warehouse depends on the scale and complexity of the data and the organization’s needs.

It is advisable to carefully consider this decision, especially in the case of Oracle JD Edwards and Oracle BI implementations.