A data warehouse is one of the most important elements of business intelligence consolidation. The data warehouse, which is also sometimes called an enterprise data warehouse, ensures that all different forms of data analysis and data reporting can be kept organized.
Definition Of Data Warehousing
Through all of the daily operations that a business has to go through in order to provide its services, it is very common that there will be more than just one source that its integrated data has to be drawn from. With the use of a data warehouse, a business can have a convenient central hub to handle all of the different integrated data streams coming from these various sources across the board.
No matter how many different nodes of historical data that a business has to analyze in order to assess its performance, the data warehouse can be used to ensure that everything is kept on the same page. With the data warehouse’s upkeep, both past data and future data can be kept in-line with what the business identifies to be its most important core directives.
Because there will oftentimes be multiple personnel who are tasked with ensuring that their enterprise has a full scope of knowledge over all data, the data warehouse can serve as a common thread between all knowledge workers to streamline their cooperation and collective analyses.
The Value Of Data Warehouse Consolidation
Though different businesses may have very different propositions and niches, there will generally be a primary operational system that serves as the nexus within which the most important data is continually uploaded; in many circumstances, this will be the sales and marketing activities that the business conducts on a daily basis.
In order for the data within the warehouse to be actionable, there is often a process of data cleansing that needs to be conducted beforehand; with the right programming, this data cleansing process can be automated before the data warehouse makes it visible for knowledge workers to analyze.
Once the data has been brought up to standard in terms of its quality, the warehouse can display everything that knowledge workers need to know in order to improve their insight. All of the key functions of a data warehouse are fundamentally programmed into its automated operations, from the initial staging process to the access layers.
Definition And Process Of Data Warehousing
The most common form of data warehouse is referred to as the ETL-based model. ETL stands for “extract, transform, load.” In the initial process, all of the raw data is taken from multiple data streams and put into position for the next stage of filtering and cleaning.
Within the integration layer, data that has been taken from these different sources is transformed in the operational data store (ODS). Following the integration, all of the different forms of data are arranged into an organized hierarchy that pays heed to their unique attributes.
The organization of data into hierarchies and categories makes it easier for knowledge workers to retrieve and understand it. Once all the data has been transformed, categorized and sufficiently cleaned, all relevant personnel in a business’s chain of command can analyze, research, and act upon the data in a well-informed manner.