A data warehouse is one of the more common topics in the IT industry. The collected data is an important source of valuable information for many companies, thus increasing their competitive advantage. More and more companies use Business Intelligence (BI) systems in their work, which quickly and easily support the analytical process. BI systems are based on data warehouses and we will talk about them in today’s article.
What is a data warehouse?
A data warehouse is one of the more common topics in the IT industry. The collected data is an important source of valuable information for many companies, thus increasing their competitive advantage. More and more companies use Business Intelligence (BI) systems in their work, which quickly and easily support the analytical process. BI systems are based on data warehouses and we will talk about them in today’s article.
Characteristics
There are four main features that characterize a data warehouse. These are:
- Subject orientation – the collected data is organized around main topics such as sales, product, or customer;
- Integrity – the stored data is uniform, e.g. in terms of format, nomenclature, and coding structures. They are standardized before they reach the warehouse;
- Timeliness – the data comes from different time frames, it contains both historical and current data;
- Non-volatile – the data in the warehouse remains unchanged. The user cannot modify it, so we can be sure that we will get the same results every time.
Architecture and operation
In the architecture of a data warehouse, four basic components can be distinguished. Data sources, ETL software, the appropriate data warehouse, and analytical applications. The following graphic shows a simplified diagram of that structure.
As can be seen from the graphic above, the basis for building each data warehousing system is data. The sources of this data are dispersed – they include ERP, CRM, SCM, or Internet sources (e.g. statistical data).
The downloaded data is processed and integrated and then loaded into a proper data warehouse. This stage is called the ETL process, from the words: extract, transform and load. According to the individual stages of the process, data is first taken from available sources (extract). In the next step, the data is transformed, i.e. processed in an appropriate way (cleaning, filtering, validation, or deleting duplicate data). The last step is to load the data to the target database, i.e. the data warehouse.
As we mentioned earlier, the data collected is read-only. Users call data from the data warehouse using appropriate queries. On this account, obtaining data is presented in a more friendly form, i.e. reports, diagrams, or visualizations.
Main tasks
As the main task of a data warehouse, analytical data processing (OLAP, On-Line Analytical Processing) should be distinguished. It allows for making various types of summaries, reports, or charts presenting significant amounts of data. For example, a sales chart in the first quarter of the year, a report of products generating the highest revenue, etc.
The next task of that tool is decision support in enterprises (DSS, Decision Support System). Taking into account the huge amount of information that is in the data warehouses, they are a part of the decision support system for companies. Thanks to advanced analyses conducted with the use of these databases, it is much easier to search for dominant trends, models, or relations between various factors, which may facilitate managerial decision-making.
Another of the tasks of these specific databases is to centralize data in the company. Data from different departments/levels of the company are collected in one place. Thanks to that, everyone interested has access to them whenever he or she needs them.
Centralization is connected with another role of a data warehouse, which is archiving. Because the data collected in the warehouse comes from different periods and the warehouse is supplied with new, current data on an ongoing basis, it also becomes an archive of data and information about the company.
Summary
Data warehousing is undoubtedly a useful and functional tool that brings many benefits to companies. Implementation of this database in your company may facilitate and speed up some of the processes taking place in companies. An enormous amount of data and information is generated every day. Therefore, data warehouses are a perfect answer to store this information in one, safe place, accessible to every employee. If you want to introduce a data warehousing system to your company, check our product Data Engineering.
Bibliography
[1] https://www.oracle.com/pl/database/what-is-a-data-warehouse/
