Real-Time Financial Data Analysis with In-Memory Computing

Data is critical to the success of financial services companies. Market data, customer data, trade data, and compliance data are retained, processed and analyzed to help firms not only stay afloat but also ahead of the competition. During this webinar, we will discuss the different types of financial data, ways financial and fintech companies process it, and show how in-memory computing is used to instantaneously analyze and make decisions based on internally and externally available data.  We will discuss:

  • Support of structured and unstructured data
  • Use cases of data types most suitable for in-memory computing
  • Performance, scalability and security related to data processing
  • Data streaming, encryption and high availability
  • Case studies of various implementations of inmemory computing used for data analytics

At the end of the webinar, you will have a better understanding how financial institutions are using GridGain’s in-memory computing platform to achieve extreme performance and scalability despite the explosion in data growth. You will also understand how to extract business value from data in the most efficient way possible.

Presented by
Eric Karpman
Consultant, GridGain
Matt Sarrel
Director of Technical Marketing at GridGain Systems

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