Data analysis – Big Data.
We analyze
the data
We draw
conclusions
You make the best
business decision
We make
jedgements
Analizy danych world map Analizy danych world map Analizy danych world map
We are data analysis experts.
  • We acquire, organize, store and process structured
    and unstructured data.
  • We analyze multidimensional data, extract knowledge from complex data structures and represent them in IT systems.
  • We use mathematical, statistical and IT methods and tools
    to analyze key data in the analysis of social or economic phenomena.
  • We build forecasting and simulation models with reference
    and in the context of socio-economic phenomena.
  • We draw conclusions, we formulate opinions based on collected data.
We analyze data to optimize your business solutions. We adapt the methods of presenting the results to your requirements. We provide 12 months for warranty on our services.
Medicine and pharmacy
Finance
Marketing and sales
Economy
Analizy danych - oferta
Our offer:
Analysis of customer migration / migration risk (Churn models).
The Churn model is a resignation from a service / product. The purpose of the analysis is to identify customers who are at risk of leaving. Commonly used models in the Churn analysis can be divided into two families – either of classification models (client at risk of leaving/client not at risk) or family of models in which exact probability of leaving is estimated.
Customer loyalty models - the opposite of Churn models.
It allows you to determine the likelihood of customer staying and factors influencing loyalty.
Sales forecasting
Credit risk analysis, scoring models (credit scoring, for the banking industry).
Credit risk should be considered in the context of a single loan agreement and the entire loan portfolio. Expert systems, scoring systems, rating systems, neural networks, logit models, AD models, KMV models, CreditMetrics, CreditRisk serve this purpose.
Insolvency risk models (debt service industry).
Fraud detection models.
Models allow to detect frauds and identify potential fraud using statistical multidimensional models. Prediction models used in data mining, based on the history of multiple operations collected in the company's databases, allow to identify key risk factors and estimate the risk indicator forecast (abuse probability) for each client (each transaction). Fraud detection analyzes are applicable in the insurance, telecommunications, banking (credit card, e-commerce), scientific or medical industries.
Mortality risk models (research pharmaceutical industry).
A number of methods in the field of biostatistics are devoted to them. A popular example of the application and use of models of this class is the constantly improved EuroSCORE system (European System for Cardiac Operative Risk Evaluation), based on, among others on the idea of logit models.
Data Mining.
Data
Data
structure
Data
processing
Dependence
analysis
Conclusions
Our recommendations.
Our team.
See also:
Statistical analyses
The higest quality in conformity with the ISI Master Journal List and FDA.
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