As the name suggests, a centralised data warehouse consolidates large amounts of data from multiple sources into a single, easily accessible format – or ‘warehouse’. As a result, data warehousing improves the speed and efficiency of accessing different data sets, which also makes it simpler for corporate decision-makers to glean insights that will directly impact their business and marketing strategies. As a result, data warehousing can help businesses stand out from competitors as well as assist in making important information more accessible.
Extract, transform and load, known more commonly as ETL, is a data integration process which brings together data from several data sources into a single, consistent data store. That information is then loaded into a data warehouse or other target system.
As the term implies, data warehousing allows businesses to combine vast swathes of data into a single location. As a result, data warehousing can increase the speed and effectiveness of accessing various data sets and make it easier for employees to derive insights that will directly influence business decisions and marketing strategies.
There are four main types of data models in the data analytic sector – hierarchical, network, entity-relationship and rational.