Data provisioning made easy for motor vehicle manufacturer

Employees of a German automotive manufacturer were dependent on data from internal systems, where they must be able to query information on production orders, quality measurements and material availability. The accuracy and coherence of this information depended largely on how the data is prepared and provided, and inadequate data up-to-dateness could lead to errors and delays. With a company that relies on the provision of data, efficiency and susceptibility to errors are the basis for planning their Business Intelligence (BI) solutions.

‍

The automotive manufacturer looked at new technologies to help them process their data with minimal effort while able to provide reliable and useful data efficiently whenever needed. Their employees in the production department should be able to access the relevant information as quickly and easily as possible. While connecting their self-service BI tool (QLIK) directly to the operational data sources of the production applications was not an optimal solution to their challenges, they decided to set up a new data warehouse (DWH) specifically for production, which serves as a data source for QLIK. To implement the data warehouse, Microsoft SQL server was chosen as a cost-effective and proven platform within the IT department.

The automotive manufacturer decided to work with the biGENIUS Desktop App, because it is able to generate the entire data warehouse automatically — from the connection of the data sources (operational applications) to the data provision for reporting. The biGENIUS Desktop App generates transfer tables (staging area layer) in the SQL server to the connected data sources, transfer procedures for collecting the data from the source systems, preparing them, saving them in the SQL server (ODS and core layer) and providing them to the BI tool (mart layer). In doing so, the copied data could be visualized via the dashboards of QLIK. Due to the procedures generated by the biGENIUS generator, these data copying and data preparation processes take place automatically in the execution plans, thereby ensuring that the data is always up-to-date, and the data quality is in accordance with defined specifications for each data object. Errors in the data supply could also be detected and rectified in a timely manner via monitoring.

‍

In order to ensure the availability of data in the data warehouse, biGENIUS users work closely with the individual departments of the automotive manufacturer. New data sources or new data objects are first connected in the development environment, then in the test environment. Following the approval from the respective department, changes are imported into the production environment where the periodic loading jobs are set up scheduled as required, to guarantee all data requirements of the departments involved have been met. In addition to selecting and generating the interfaces for the relevant data for the individual areas, the frequency at which this data can be updated, provided, and retrieved was also crucial. The automotive manufacturer currently uses these short-cycle data updates in logistics, where open transport orders from a certain area are displayed on large screens on the ceiling

1. With biGENIUS, high volumes of data can be quickly evaluated by the data warehouse without disrupting operational applications. For the different departments in the automotive manufacturer, the prepared data copies are automatically available to them with an update frequency required for their analysis. With this foundation, they are now able to make targeted decisions with a significant increase in efficiency that is reflected in their improved customer satisfaction.

‍

2. The simple connection of the data sources to the data warehouse and the data visualization in the QLIK dashboard enabled additional and flexible evaluation of their data for their employees. With biGENIUS, they can now access all relevant information interactively and with just a few clicks, effectively model new data sources in their data warehouse, and able to evaluate the data with QLIK.