Data Management

Data is becoming an increasingly central asset for financial institutions. Depending on the manner in which data is treated, companies may be fighting data quality issues and experiencing high maintenance costs – or they may be able to gain insight, support their decisions, generate opportunities and respond to market and regulatory pressures with a help of new generation of data analytics and business intelligence.

DataArt helps its clients convert data from a third class citizen to a valuable asset that can transform business reality. Cutting edge technology and financial services expertise position DataArt as an outstanding partner to deliver innovative solutions that address a wide range of aspects - from defining data management strategy to designing solutions and modeling processes, to migrating data, automating quality assurance and promoting user adoption. 

Particular areas of DataArt expertise in financial services data management

  • New generation of data warehouse / BI solutions, which allow buy-side firms to implement timely and flexible reporting and analytics to support decisions and operational processes across all business segments
  • Federated master and reference data management systems, which link previously disparate departmental data systems, enabling efficiencies, better products and analytics as well as business benefits such as a single view of a customer;
  • Innovative data governance solutions that promote a new business culture of data ownership by business stakeholders and make it possible to achieve transparency through data lineage and new levels of data quality;
  • Semantic and graph data management systems, or wide Data, allowing financial enterprises to achieve dynamic data modelling, data linking and enrichment, incorporate semi-structured and unstructured data and achieve better insights via powerful analytics, including text and predictive analytics;
  • Big data / big data analytics projects for financial enterprises. DataArt big data expertise ranges from large-scale data processing systems delivering analytics to low-latency distributed in-memory solutions supporting pricing and risk engines. DataArt has also recently built strong Hadoop to Spark migration capability, which is relevant for financial companies that have started implementing big data projects on Hadoop and are now considering a move to the faster, more powerful and much easier to maintain Apache Spark.

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