Building Data Warehouse and Data Mining

eNET creates value on the field of data warehouses, and realted datamining, analysis.

Through building data warehouses, eNET uses open-, and closed-source tools (e.g. database engine – PostgreSQL, MongoDB, Cassandra; Big Data – Apache Hadoop (Hive, Pig), Impala; ETL – Kettle, Pentaho, Riporting – jasperServer; Ad Hoc riporting – FlySpeed; ROLAP – Mondrian, jPivot)

eNET’s data mining activity is aimed at identifying hidden correlations in the following business areas, applying strong mathematical and analytical calculations to large amounts of information provided by our clients or stored in external databases:

  • Product pricing: defining optimal pricing strategies; dynamic pricing
  • Campaign analysis: review of the return of marketing campaign costs
  • Projections: analyses of economic and financial time series
  • Product development: client classification / value calculation; product portfolio analysis and expansion based on demand estimation
  • Risk analysis: identification of credit and other financial risks
  • Optimisation: answers to resource allocation and scheduling questions
  • Classic data mining: processing, cleaning and filtering of high-volume data; displaying them as a map or a network; development of reporting systems; automated online data collection
  • Tailor-made developments: displaying analyses on user interfaces; integrating them into existing systems; creating specific algorithms

The following methodologies are used in data mining:

  • Econometric and statistical analyses (forecast, impact analysis)
  • Stochastic simulation (scenario-based examination of complex systems)
  • Market balance modelling (demand estimation)
  • Algorithm development (building of special automated systems)
  • Data mining (high-volume data processing, visualisation and assessment)
  • Network analysis (graph-based)

Our data mining service is recommended to businesses and institutions that collect masses of data which should be utilised for well-founded decision-making as well as operational and business development, taking advantage of the correlations within those data.

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