Data Science

  System Soft Technologies partners with clients in developing and extracting deep insights from their existing data. Our data scientists, with deep understanding of statistical modeling, machine learning and data mining, collaborate with in-house subject matter experts in building such insights and integrating with existing business processes and platforms.

Bringing advanced Data Science to decision-making

Start a conversation today with our data science team and learn how System Soft Technologies can help you create your best solution this year. Our Data Science team excels at delivering on-time and on-budget solutions utilizing these analytical tools in their quest to uncover secrets in your Structured, Semi, and Un-Structured data:

  • R programming
  • Microstrategy
  • SQL
  • Spotfire
  • Python
  • IBM Cognos
  • Hadoop
  • SAP Business Objects
  • Java
  • Oracle OBIEE
  • Hive
  • SAP HANA
  • MATLAB
  • Spark

Data Science solution accelerators

Many components of developed business intelligence tools are appropriate of re-use in other, similar projects. Starting with a tested, proven solution and building on this foundation allows our engineers to customize the data science solution to meet the needs of any client mandate – with time to spare.

Our teams are especially adept at building quantitative processes that are the foundation of our analytics platforms, and thus make our solutions more effective. We focus on helping the client leverage all available sources of data to achieve higher performance of their programs and systems, from data generated by their customers to information originating in operations and their supply chain.

Our internally developed accelerators, coupled with the strong business process focus our experts bring, allow us to efficiently implement Business Intelligence tools for our clients. The results:

  • A customized, business focused solution that increases customer and end user-business insights.
  • Increased value and competitive advantage.
  • Sophisticated level of analytics which satisfies data scientists’ requirements.
  • Level of ease-of-use that satisfies non-technical business users.

Critical Thinking. Collaboration. Success.

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