You might have heard of the term “data warehousing” before but have not really understood what it actually means or its concepts, other than a mental image in your head of a physical warehouse full of computers and bits of binary code being off strange-looking contraptions, with computer boffins reading those printouts and scratching their heads in confusion (it was certainly my mental image when I first heard the term)!
Well if you have just heard of this term and are intrigued to find out a bit about what it means and whether it could be something your business could adopt, continue reading to find out more!
An introduction to data warehousing
In a nutshell, a data warehouse is basically a relational database which has been designed for queries and data analysis, rather than for transaction processing (which is what a database typically is).
Although it will comprise of historical data which has been supplied from a transactional database, it can also include data from other sources too. The purpose of a data warehouse is to separate the workload from a transactional database server, and equally as important, it also enables businesses to completely consolidate data from many different sources.
Data warehouses include an ETL (extraction, transformation and loading) solution, which is basically the process of extracting data from external sources, transforming that data into a useable source to fit the operational needs of the data warehouse, and then loading that transformed data into the data warehouse ready for query and data analysis.
What else can a data warehouse do?
A data warehouse can also perform some other clever stuff too. We know so far that it can pull data in, transform it into something usable and then set it up ready for analysis, but a data warehouse can also obviously perform queries on it using something called an OLAP (online analytical processing) engine.
An OLAP engine in layman’s terms is a method of performing multi-dimensional queries very quickly. For example, a single-dimensional query might be to check how many people bought a particular product on a given day, but a multi-dimensional query might be to check what times people purchased that product, whether they also bought related products at the same time, how they paid for them and whether they bought similar items in the past 6 months.
Of course, you need a way to be able to interact with a data warehouse and so data warehouse solutions also come with client analysis tools, as well as other useful tools to help a business manage the process of gathering, reporting on and delivering that data in a useful format.
Do I need a data warehouse solution?
If you work with “big data”, that is, information that is of such a vast quantity that it is often too complex for typical relational databases to perform queries on, then yes you do need a data warehouse solution!
Data warehouse solutions such as the Oracle Exadata offer a great way to perform such complex and resource-intensive analysis on your data, so that you can ensure that your business stays ahead of the competition and has that all-important edge to them!