Systematic Customer Comparison based on Meta-Data

Aspera is a software company mainly based in Aachen. Aspera offers three solutions namely: SmartTrack, SAMi and SLC. It has more than 200 clients and specializes in license management. It assists in the calculation of license demand and creates lots of potentials for saving. It is interesting how customers use these solutions. It might be worth knowing if there are some patterns existing in databases used by different clients.

Of course we cannot use client database directly. We are using a framework from Martin Kuehn’s thesis titled ‘A metadata-based approach for generation of performance test data’. Martin in his thesis developed an application called MADSE(Metadata analysis and data synthesis environment). MADSE extracts qualitative and quantitative characteristics of a database and creates a synthetic dataset that imitates the production databases. The output of Madse is a JSON file which can be viewed in HTML as well. This JSON file will be the starting point for my thesis.

MADSE gathers statistics and information about a single client only. It is possible to gather information from multiple customers and determine what is interesting to us. We can perform analysis on these data and detect patterns.

The goal for my thesis is to develop a process that can use MADSE for extraction of information from various customer databases, convert information to a usable format and perform different analysis on the derived data. We can visualize data of different customers and find patterns between them. Similarly, we can find patterns among different Aspera solutions, and determine how database usage differ within these solutions.

Project information



Thesis for degree:



Presha Rajbhandary