What is a Data Warehouse?

A Data Warehouse is the term given to a set of data specifically structured for query and analysis, in other words the data in the warehouse has been prepared for ease of access, thus allowing information and knowledge to be extracted. The ease of reporting is the key to the success of any data warehousing system.

Data warehouses provide for both simple tabular reports as well as detailed "formal" reports, thus allowing for all forms of reporting requirements.

It should be noted that the form of the data (relational database, flat file etc) is unimportant, it is the fact that the data is accessible and in continuous flux that makes it a data warehouse.

Contemporary can offer your business both the applications and the training on the full range of data warehousing products.

Some Data Warehouses May Not Be Used by Decision Makers.

Some pundits have declared that Data Warehouses are rarely used for decision making purposes, rather they are used to monitor the results of previously made "strategic" decisions, others disagree. Most do agree that the data is being held in a way that supports ease of access and is structured with a view to support query and analysis which offers tremendous power to businesses today.

Data Warehouses & Business Intelligence

Many confuse the Data Warehouse with the conversion of data into Business Intelligence and this is simply not the case, the data warehouse is merely a container for the data of a business, it is the tools that query it and then process the basic information (in the warehouse) that convert that data into understandable information and hence to "knowledge". Data warehousing is thus one step on the path to full Business Intelligence.

Why Are Data Warehouses Created?

One simple reason is that the separation of the systems that carry out transactions from those that are queried about past transactions allows each system to "concentrate" on its own job. This can be especially important for organisations where it is imperative that all transactions are carried out in acceptable amounts of time. The splitting of the systems therefore allows each system to have a higher probability of meeting their response targets.

Another reason, is that some methods of data modeling used to speed up query and reporting are not appropriate for transaction processing as the modeling technique slows down and complicates the transaction process, which as above may not be acceptable in some instances.

Data Warehousing As a Means of Cleansing Data

Another use of the data warehousing system is to allow for the cleansing of data. It is often easier to capture transactions, apply any cleansing techniques and then feed the clean data back to the separate transactional data system. This can be a much simpler way of cleaning data as it does not require changes to the transactional systems, merely the means to alter the data held in that system.

Frequently Asked Questions

What is data warehousing?

Q: What is a data warehouse?

A: OK, first and foremost as the name suggests when we think about a warehouse it’s a large building with lost of things in it. When we think about a data warehouse we're talking about collecting together data from our business and putting it into one place so that it is easily accessible. We can take it one step further because the data that we put in that warehouse we need to be able to trust it so we can go on and talk about data cleansing and data reliability and those various areas.

Q: Do I have to build a data warehouse to get business intelligence?

A: OK, that’s a question that comes up quite frequently, in reality the simple answer is no you don’t have to. It’s about what you in your organisation need to do. A data warehouse is just a term, it describes a collection of data you might need to use to answer a particular question.

Q: I have heard of data marts- what are they?

A: Well again, data marts along with data warehousing are just industry terms coined a number of years ago and used interchangeably.  A data mart generally is a smaller more business subject focused set of data, maybe that focuses on marketing analysis rather than a data warehouse that will cover the data for the whole business. Quite often data marts are built from data warehouses or you will build several data marts that will make up a data warehouse.

What is dirty data?

Q: What is dirty data?

A: The simple statement dirty data is data that you don’t trust to make a decision. There can be many reasons for that, for example the data maybe incomplete, you may have 5 lines of someone's address but you have 4 missing. It maybe that the data has been incorrectly entered so the title may have been entered into the first name in the surname box. May be your data is stored in different ways in different systems, so you might be taking data from here which is in sterling and data from here which is in euros- you can't use this, it would have to be converted. These are just some examples of dirty data and in all cases it has to be cleaned before it can be trusted.