Smart About Risk  
data analysis

Big data analysis

Modern technologies and gradually decreasing costs of data storage are making generating and archiving of digital data easier. But how to generate the highest added value for your company from the stored data?

Advanced Risk Management, s.r.o., would like to offer you consulting services in the area of big data processing (this term can be defined e.g. as an amount of data which cannot be smoothly processed by tools like MS Excel). Using own software solutions or commercial tools and using mathematical statistics, advanced mathematical methods and own expert opinion.

ARM offers services mainly in following areas:

We offer mainly following services

Design of data collection system

Data collection method affects to a large extent the subsequent explanatory value of information gained from this data. Therefore, it is necessary to focus on this area and collect data in a way to make them usable for further analysis.

  • Creation of methodology for data collection, processing and evaluation.
  • Designing the structure of collected data.
  • Setting up the data collection process.

Revision of existing data processing system

The digital data area is developing quickly, and therefore it is necessary to update also the procedures of data processing and data evaluation.

  • Evaluation of methodology for data collection, processing and evaluation.
  • Data quality assessment via performing logical, type and content checks based on own know/how and/or based on client requirements.

New possibilities of data utilization

How to utilize the data we have available? How to gain higher quality information from them, or information we do not have available now? Can we get information leading to an increase of sales, sales proceeds and profits or to a decrease of costs from the data we are currently collecting?

  • Discovering structure in unstructured data and converting them into client-defined database.
  • Creation of tools for prediction of financial an non-financial variables.
  • Detecting marketable values in the data.
  • Creation of optimization models in order to increase capacity utilization, decrease costs or increase production efficiency, etc.