We focus on the implementation of projects and the implementation of data processing solutions, mainly for the following areas:

  • creation of data warehouses
  • data integration (ETL)
  • data quality
  • creation of reports, analyses, statistical overviews
  • OLAP modelling
  • open data
  • consulting services

Implementation of concepts and methodologies that improve the decision-making process in enterprises and in institutions in various branches of industry or public administration.

BI - Business Intelligence is a comprehensive set of methodologies, tools, data and a flexible user interface and represents one of the most important factors in the quality of business informatics and related shifts in the competitiveness of companies. Business Intelligence has several basic principles, namely the transformation of data from transactional and production systems into analytical data, which are then used for effective decision-making. BI solutions are based on the multidimensionality of data storage and processing referred to as OLAP.

The implementation of projects for BI solutions is usually focused on the following parts:

  • creation of temporary and operational data repositories, extracted data
  • implementation of transformation tools with support for data quality management
  • data warehouses with a logical data model for long-term data storage
  • tools for creating user reports, reports, statistics and advanced analyses
  • data-mining models for advanced data analysis, the use of solutions for data science and elements of machine learning

Creation of methodologies for the operation and maintenance of complex solutions focused on data processing.

A proposed solution consists of three basic logical units:

  • Preparation of data from the system, definition of rules for data acquisition, data extraction and pre-processing. This part requires the configuration and implementation of extraction procedures on the side of a specific system. These procedures do not affect the processes running in the system and do not affect the existing implementation of the solution in any way. The defined data extraction time is selectable and is usually set so that the procedures run at night.
  • Data storage in the database (statistical data) is fully automated and ensures continuous preservation of extracted data. The data model of the database is set up so that it is extensible while facilitating expansion and modification. The database provides statistical data for the desired outputs and data areas for their valuable visualisation.
  • Users access the data stored in the statistical database (DWH - data warehouse) through a web interface. Access to data is controlled based on data area permissions. Permissions can be changed dynamically. The solution contains predefined data structures that allow users to create their own statistics immediately.

Deployment of a tool for creating and displaying statistics and reports which facilitates:

  • Access to statistics through an intuitive graphical interface based on a thin web client. This interface also enables the development of reports.
  • Login and navigation in the environment using an Internet browser. After logging in, the user access to objects is regulated by permissions, which can be changed depending on the customer's needs.
  • Creation of statistics containing custom controls based on data stored in the data warehouse (DWH). Interactive control provides dynamic changes in the display of individual objects on the screen. The application of filters is intuitive and can be changed at any time.
  • Display of detailed data for export of given records, for example in Excel or PDF format. The filters used in the given report are applied to the displayed data, thus it is possible to create a set of data for further processing.

Method of implementation

In order to verify the appropriateness of deploying the solution over the data available in a company and to better define the requirements of the solution, we generally suggest implementing the functional requirements in the following steps:

  • Verification of the means for obtaining data from source systems.
  • Use of the option to store data in a data warehouse.
  • Creation of the initial data set.

The outcome is an implementation plan with a schedule, defined cooperation and the architecture of the future solution.

An overview of the activities required to put the solution into functional testing:

  • Installation of the solution with the option to use existing licenses for the database server and existing HW resources.
  • Implementation of the connector to the source systems, or adequate provision of data transfer to the new solution.
  • Implementation of data processing processes and storage in the data warehouse with the supplied data model.
  • Creation of a data set according to customer requirements.
  • Configuration of data access security.
  • Delivery of output reports, dashboards or analyses.

Delivery also includes basic project documentation with a description of the solution and staff training.