Data warehouses

Data collection

Data warehouses are an essential element of a company IT system. Organized data provide basis for all sorts of analyses and reports – that is provision of access to all the information used in the company.

Comarch Business Intelligence enables collection and safe storage of information in data warehouses, generation of various analyses, as well as simple and user-friendly acquisition and transformation of data from various sources. Usually, data are loaded from numerous source systems, data warehouses or even individual flat files during the lowest workload of sources, using ETL process.

Data quality

Part of the data loading process is Data Quality process, which ensures its quality. Many times, the human factor causes incorrect analyses, which entail wrong decisions. Analyses could include duplicate items, language errors, or simply missing data, etc. 

Such inconsistencies and errors in the data are eliminated in the Data Quality process, via complete validation of the analysed data – which gives us greater certainty of data correctness. Usually, this involves sets of formal and business principles which describe the given processes occurring in a company.

Area of analyses

This term is related to analytical areas and multivariate analyses. A common solution in this respect is OLAP, that is an analytical cube. This allows data to be efficiently processed, as well as stored in business-comprehensible models, based on facts, measurements and dimensions.

Comarch Data Warehouse Manager - DWM

This element of Comarch Business Intelligence combines all the modules used to integrate and manage data warehouses. The purpose of Comarch DWM is support and supervision over the process of warehouse feeding, administration, organization and description of individual data. Application of individual modules depends on the specificity of the given project, quantity and diversity of the data sources, as well as the needs of the customer. 

Functions of the Comarch DMW application include:

  • Data warehouse structure management,
  • Loading process and transformation management,
  • Logging of events during loading and transformations and informing the administrators,
  • Supervision and processing, additional mappings, groupings, divisions, and maintenance of dictionaries in additional data sources.

Read more: Data Warehouses

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