Data management involves the development and execution of all schemes, policies, practices and procedures necessary in order to manage the data of an enterprise in the most effective way. It is important to realize that behind data analytics are the data themselves. Put simple, one must never underestimate the significance of well-structured and high-quality data.

In fact, you probably have many important data scattered in many different places. What might be missing from your business, are data management best practices that could help you access all your data and take a closer look at them. Doing that may open your eyes to hidden patterns, opportunities and new ideas thus boosting your company towards success.

Our data management process is in line with the following principles:

  • Requirement analysis: Capture the requirements of relative business processes and define the data requirement needs
  • Intelligent Data Storage: Design and development of databases for data storage and processing
  • Data Integration: Combine and interpret structured and unstructured data from different and heterogeneous sources
  • Data Quality: Perform data cleansing, harmonization and quality validations. Assure data completeness, consistency, relevance and accuracy
  • Interoperability: Ensure the exchange and use of information between various systems
  • Compliance with regulations/legislations: GDPR, Basel III, Sarbanes- Oxley, Statistical Confidentiality