Data modeling - consistent data analysis for your BI platform

Once a BI strategy has been developed, its implementation must be designed – based on the current, company-specific circumstances. In the first step, we therefore analyze the existing system environments, the data content, the data availability and the data quality (usability) of the source systems. Then, based on the results, we develop possible optimization proposals in terms of infrastructure, data modeling (physical and logical), data integration, and the analysis of your data (data usage).

A first and fundamental step of the conception phase is the development of a uniform and consistent data model. Our data modeling methods for data warehousing ensure exactly this and allow you a comprehensive, interactive view of products, customers, regions and other information characteristics. Our OLAP-based solutions enable fast, complex queries, a variety of ways to display your data, and individual and trend analyses.

The AIC Group works with both Star and Snowflake schemas in data modeling. Both are complex, logical architecture systems in data modeling with variable query options of the data stocks.

The relational data storage of facts and dimensions in OLAP systems provides any number of possible combinations of information. In the mass of data, key figures and properties are condensed on the highest hierarchy level and thus represented as a multidimensional structure – as a star schema. The advantages of data representation as a star schema are the simple, intuitive data model and the relatively low maintenance effort of your data warehouse.

With the Snowflake schema, on the other hand, the dimension tables are represented in a normalized way. Unlike the Star schema, where the surrounding dimension tables are all directly linked to the fact table, the Snowflake schema has multiple levels. The data is thus less redundant and better structured.