Data modelling and performance

AIC Group cares for an integrated and consistent data transfer into the dispositive system (Data Warehouse). We evaluate existing system surroundings and develop possible optimizations concerning infrastructure, data modeling (physically and logically), data care (ETL) and performance based on the results. Our data modeling methods for Data Warehousing lets you have a comprehensive, interactive view of products, customers, regions and information characteristics. Our OLAP-supported templates consist of fast, complex queries, whereas a huge number of styles of your data as well as single and trend analyses is possible.

Data modeling via star pattern

You receive as many possible combinations of information as you like by relational data of facts and dimensions in OLAP systems. The mass of data condenses key figures and characteristics numbers and qualities to the highest hierarchy steps and displayed as a multidimensional structure –a star pattern. The advantages of data representation as a star pattern lies in the easy, intuitive data model and the relatively low servicing costs of your Data Warehouses.

Data modelling via Snowflake pattern

Dimensional tables are shown normalized in a Snowflake pattern. In contrast to the star pattern where surrounding dimension tables are connected directly to the fact table, there are several levels in the Snowflake pattern and dimension tables are disassembled into smaller dimensions. Data is therefore less redundant and better structured.

AIC Group works with both star as well as Snowflake patterns in data modelling. Both are complex, logical architecture systems in data modelling with variable enquiry options of the data.