Detect correlations among data. Identify whether desired values are correlated with other values; you can determine strength and character of these correlations. Create analytic sets of data.
Analysis of interdependencies analysis allows the user identification of data that is intrinsically linked. Economic, market or social phenomena are correlated in an unobvious way and Big Data analysis makes that we find an answer to queries that refer to factors having an influence on analysed process or phenomenon. Moreover, we investigate whether and how phenomena and processes are correlated with each other and what time lags are between them.
Aggregation of variables makes possible setting aggregate parameters that may refer to listing frequency, time range and content of databases. Therefore, it is possible to set search parameters in order to choose data connected with specific area (e.g. unemployment rate), listed long enough and then we can transform data found according to a specified time interval (e.g. we transform data into a monthly data). As a result, data exploration by means of the interdependency analysis is fast, comfortable and adapted to individual needs.