According to Bill Inmon, “a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.”
The data warehouse is the beating heart of the Intelligent organization and it serves different vital goals that focus on:
1. Improving integration
An organization registers data in different systems, which support the various business processes. In order to create an overall picture of business operations, customers and suppliers – thus creating a single version of the truth – the data must come together in one place and made compatible. Both external (from the environment) and internal data (from ERP, CRM and financial systems) should merge into the data warehouse and then be grouped.
2. Speeding up response times
The source systems are fully optimised in order to process many small transactions, such as orders, in a short time. Creating information about the performance of the organization only requires a few large ‘transactions’ during which large amounts of data are being gathered and aggregated. The structure of a data warehouse is specifically designed to quickly analyze such large amounts of data.
3. Faster and more flexible reporting
The structure of both data warehouses and data marts enables end users to report in a flexible manner and to quickly perform interactive analysis on the basis of various predefined angles (dimensions). They may, for example, with a single mouse click jump from year level – to quarter – to month level and quickly switch between the customer dimension and the product dimension whereby the indicator remains fixed. In this way, end users can actually juggle with the data and thus quickly gain knowledge about business operations and performance indicators.
4. Recording changes to build history
Source systems do not usually keep a history of certain data. For example, if a customer relocates or a product moves to a different product group, the (old) values will most probably be overwritten. This means they disappear from the system – or at least they are very difficult to trace back. That is a pity because in order to generate reliable information, we actually need these old values, as users sometimes want to be able to look back in time. In other words: we want to be able to look at the organization’s performance from a historical perspective – in accordance with the organizational structure and product classifications of that time – instead of in the current context. A data warehouse ensures that data changes in the source system are being recorded, which makes historical analysis possible.
5. Increasing data quality
Stakeholders and users frequently overestimate the quality of data in the source systems. Unfortunately, source systems quite often contain data of poor quality. When we use a data warehouse, we can greatly improve the data quality, either through – were possible – correcting the data whilst loading or by tackling the problem at its source.
6. Unburdening operational systems
By transferring data to a separate computer in order to analyze them, we unburden the operational system.
7. Unburdening the IT department
A data warehouse and Business Intelligence tools allow employees within the organization to create reports and perform analyses independently. However, an organization will first have to invest in order to set up the required infrastructure for that data warehouse and those BI tools. The following applies: the better the architecture is set up and developed, the more complex reports users can independently create. Obviously, users first need sufficient training and support, where necessary. Yet, what we see in practice is that many of the more complex reports end up being created by the IT department. This is mostly due to users lacking either the time or the knowledge. Another reason may be that the organization did not put enough effort in developing the right architecture.
8. Increasing recognisability
Indicators are ‘prepared’ in the data warehouse. This allows users to create complex reports on for example returns on customers or on service levels divided by month, customer group and country, in a few simple steps. In the source system this information only emerges when we manually perform a large number of actions and calculations. Using a data warehouse thus increases the recognisability of the information we require, provided that the data warehouse is set up based on the business.
9. Increasing findability
When we create a data warehouse, we make sure that users can easily access the meaning of data. (In the source system, these meanings are either non-existent or poorly accessible.) With a data warehouse users can find data more quickly and thus establish information and knowledge faster.
All the goals of the data warehouse serve the aims of Business Intelligence: making better decisions faster at all levels within the organization and even across organizational boundaries.