In Business Intelligence, not only data modeling is important but also the commonly used term ETL. But what exactly is an ETL? ETL stands for Extract Transform Load, which means that the source data that is not always directly suited to present without further editing in a dashboard or visualization is first processed raw to easily import or load. In most cases, a Business Intelligence solution does not work with pure relational data models with models like the frequently requested data source or star models. A star model or data field is the first step to reaching a final result for the dashboard. Which model is most useful to use depends on multiple factors. How many data or records should be read?
Is all data actually available in the DWH (Data Ware House), or is there any need to add the in-memory data model of the self service BI tool directly to the presentation? In short, questions that the modern Business Intelligence tool and the experienced BI developer should take into account? A consideration of the amount of data to achieve a well-functioning dashboard that is user-friendly for end users and quickly displays those results where it is developed. There are several self-service BI packages available, well-known tools include Cognos Powerplay, Tableau, MicroStrategy, SAP Lumira, Talend, SiSence, Oracle BI (OBIEE) or Microsoft BI (MSBI). Everyone works more or less with interstitials of Cubes or Datamarts. Different names for a format of the data generated after ETL and which of the chosen solution can be used to present the dashboard. With the arrival of the Qlikview Sense release, Qlikview has given a completely new look and feel to the well-known Self Service Tool. A Self Sevice BI solution that will be discussed in the coming years.