Megoldásaink - Big Data, üzleti intelligencia, adattárház
Big Data, Business Intelligence and Data Warehouse

Our experience shows that the need arises to have Business Intelligence quite soon after implementation in the users of systems processing mass data. Requirements come up to automatically analyze data stored in the system, to make reports and dashboards, to exchange standard data without users’ intervention, to create interfaces. For the BI layer it is practical to create data marts that serve the reports and dashboards directly. We use Big Data tools to handle unstructured mass data, and the results are loaded into data warehouses and data marts. By stream analysis we make it possible to process and analyze mass data online. In this case data go straight from the source to the analysis tool (e.g. Power BI).

Our solutions have been introduced successfully to various clients. Our technological repertoire is quite diverse, we use Oracle and Microsoft SQL Server Database, different BI tools (MS PowerPivot, Power BI, MS Reporting Services), and in case of our Big Data solutions both on-premise (e.g. Cloudera or Hortonworks) and cloud-based (e.g. MS Azure or Google) solutions are available.

Meta-data driven data warehouse – Allianz Hungária Zrt.

Allianz logo

Implementation of meta-data driven data warehouse, building of data marts for the processes of different divisions. Ad-hoc quiry and BI analysis tools were connected. We built a Big Data cluster to handle unstructured mass data and – with the help of an ETL tool – we integrated it into the central data warehouse.

Central Address Registry – Ministry of Interior

Belügyminisztérium logo

The aim of the Central Address Registry project was to create the regulatory environment and the administrative process of Hungarian address handling and to achieve a complete, authentic address database. Our job was to implement the integration between the Personal Data and Adress Registry and the Central Address Registry, where we used data warehouse technologies and methods to execute transformation among data groups with logically unbundling functions (STAGE, PREPROCESS, DW layers).

Data processing and analysis – Bank360 Zrt.

Bank360 logo

Live and scheduled Bid Data data processing and analysis based on Microsoft Azure cloud technology and lambda architecture. Each component is cloud-based, which makes local hardware resources unnecessary and creates scalable, reliable and disaster-tolerant solutions in the cloud. Data analysis and visualization happens in PowerBI, where live and past incidents can be followed and analyzed. Azure Stream Analytics handles constantly incoming mass data and leads towards real-time streaming (PowerBI) and archive storage (Azure Blob Storage). Each business incident is archived at low cost in the cloud, making data analysis possible in the future. Archive mass data processing is done by Azure Data Factory and then processed data get to Azure SQL Database. Analysis and visualization is performed by PowerBI.

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