Business intelligence (BI) is a process for the systematic collection, analysis, and visualisation of business-relevant data from ERP systems and other databases. The extracted data is transformed and integrated into a data warehouse (ETL process). With the inclusion of analytical reporting and aggregation of relevant metrics, company-specific reporting is achieved. Thanks to BI, action-oriented knowledge is generated to allow informed operational and strategic decisions to be made.
The term data discovery stands for a modern business intelligence tool, which allows a high degree of user autonomy and flexibility by the discovery of data patterns (data patterns). Data discovery systems are usually based on so-called in-memory technology. This stores the data in an own local memory, so that the information is available without complex modelling and within markedly reduced processing time.
Framework or reference architecture
“Framework” refers to a programming framework, which is used in object-oriented or component-based software development as a reusable application architecture. The extensible, semi-complete structure serves as a foundation for building an application according to specific requirements.
The term "big data" refers to data sets that are so extensive that they can no longer be taken up, organised and processed by traditional database software in a timely manner. The term refers not only to the quantity, but also the diversity and speed of the data.
OLAP (online analytical processing) is a hypothesis-based method of analytical information systems. Analyst assumptions will be confirmed or refuted by requests to the OLAP system. OLAP systems obtain their data either from operational company databases or from a data warehouse. The underlying structure of the OLAP is an OLAP cube, which has been created from the operational database. (Source: Wikipedia)
Staging is a process of information integration in which the data from a data region is temporarily cached (staging area), in order to clean and transform it without further burdening the data sources. After the cleansing and transformation step, the data is loaded into a target database. (Source: Wikipedia)
A data warehouse (DWH, DW) is a database which summarises data from various sources in a consistent format (information integration). This improves the convenience of access to these data. The data is provided by the data source and loaded into the ETL process to the data warehouse, and stored there long-term, especially for data analysis (OLAP) and business decision support in companies, as well as for data mining. (Source: Wikipedia)
ETL (extract, transform, load) is a process in which data from multiple differently structured data sources is united in a target database. Extraction of relevant data from different sources. Transformation of the data in the schema and format of the target database. Loading the data into the destination database. (Source: Wikipedia)
ODAG (On Demand App Generation)
ODAG (On Demand App Generation) offers users and BI Power users the ability to load and analyse big data sources. For this purpose, the incoming data is first displayed in an aggregated view via an upstream overview application. You can then restrict the data by selecting and creating a detailed application at the touch of a button. This detail application has an impressively high performance when it comes to analysing big data.