Building and supporting corporate Data Lake | Data Warehouse

Centralized data warehouses allow organizations to store, process, and retrieve structured, semi-structured, and unstructured data in any volume. They combine structured request, profiling, data search, predictive analytics systems, and machine learning. In their turn, advanced analytics and machine learning based on structured and unstructured data are key priorities for many organizations in maintaining competitiveness. According to analysts, the global Data Warehouse / Data Lake markets will grow by 2028 on average by 10.6 and 26.4%, respectively.
 
Data Lake is a centralized repository that allows to store structured and unstructured data in any volume. It is basically a repository that stores a huge amount of "raw" data in their original format.
Data Warehouse is the only corporate repository of data structured by various parameters
 
 

Building corporate data warehouses will allow your organization to take data management to a completely new level and will give the business the opportunity to gain significant benefits for management decision-making: 

  • Scalable and secure data storage solution with advanced capabilities for analysing various types of data
  • Unhindered access to all important corporate information
  • Consolidated data catalogs, duplication and fragmentation free data due to a single data source
  • Increased and maximized value of data due to cloud analysis and computation
  • Robust foundation for the introduction of artificial intelligence and machine learning technologies
  • Implementation and development of machine learning models for predictive data analysis / predictive analytics
 
 

Metinvest Digital has experience in building corporate Data Warehouse| Data Lake for structured and unstructured data and will help your organization to: 

  • Audit the corporate data management systems
  • Develop a roadmap for building the corporate Data Lake | Data Warehouse
  • Analyse and structure data sources for Data Lake | Data Warehouse
  • Build ETL | ELT processes for data management
  • Develop and implement the forecast and optimization models based on artificial intelligence and machine learning technologies
  • Build information panels and reporting
 

 

Consultation

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