Data Science-Driven Software Product Innovation


In a digital economy, it is essential for enterprises across industries to leverage software to create compelling user experiences and deliver value-add services. In many enterprises, this manifests in the form of customer-facing mobile and web applications. In order for these applications to have maximum impact, they must continue to evolve based on how customers actually use them. To do this, these applications must be instrumented to collect data about user behavior. Then, using data science techniques, enterprises can better understand how their products are used and identify where improvements could be made.

In this webinar, two Pivotal data scientists present how they helped a large financial services company evolve one of its customer-facing applications to meet the changing behavior and needs of users. This application, which allowed customers to monitor and analyze real-time financial market data and place trades, was already instrumented to log user activity. By using clustering-based "sessionization" of each user's activity, along with topic modeling and clustering techniques, the Pivotal team was able to discover typical usage patterns that helped the organization make improvements to its application and identify anomalous user sessions to detect misuse.

This webinar examines data science-driven product innovation. Register today for your chance to learn:

  • The role of data science in application and product development
  • Why understanding user behavior is important to achieving business goals
  • How to analyze application usage data to better understand user behavior
  • How to turn those insights into new and improved application features
  • How to build a sustainable data-driven application development practice

Regunathan Radhakrishnan
Principal Data Scientist, Pivotal

Regunathan Radhakrishan is a Principal Data Scientist within the data science team at Pivotal, where he helps customers derive business value from data with a special focus on IT security, operations and fraud detection. Prior to Pivotal, he held research positions at Dolby Laboratories Inc and Mitsubishi Electric Research Labs (MERL), Cambridge. He received his M.S. and Ph.D degrees in EE from Polytechnic University, Brooklyn, NY. His research interests include statistical machine learning, video summarization, multimedia content identification, watermarking and spatial audio. He has published several conference papers, as well as 7 journal papers and 5 book chapters and a book on multimedia content analysis and security. He has filed about 40 patents in the areas of multimedia content analysis, multimedia security and content identification. He has received “The Valuable Invention Award” from Mitsubishi Electric Corporation for the work on Video summarization using Audio Analysis and has received the SMPTE Journal paper award for the work on Audio-Video Synchronization.

Srivatsan Ramanujam
Principal Data Scientist, Pivotal

Srivatsan Ramanujam is a Principal Data Scientist at Pivotal where he executes Data Sciences labs for customers with a special focus on text analytics. Previously, as a data scientist at Sony Mobile Communications in Redwood City, he lead Sony Mobile's Data Science initiatives that spanned across Statistical Machine Learning and Natural Language Processing. Before joining Sony, he was an engineer in the analytics team at Salesforce. He received a Masters in Computer Sciences from UT Austin, completing his thesis and research in NLP where he focused on graphical models for weakly supervised sequence prediction problems. He loves mountaineering and is a native speaker of Python.


Jeff Kelly
Data Evangelist, Pivotal

Jeff Kelly is a Data Evangelist and a member of the data product marketing team at Pivotal. Jeff spends his time researching and writing about trends in the data market—including the intersection of Big Data, cloud and application development—for the benefit of Pivotal’s customers and internal stakeholders. Prior to joining Pivotal, Jeff was the lead industry analyst covering Big Data analytics at Wikibon, an open source research and advisory firm. Before that, Jeff covered the data warehouse and business intelligence markets as a reporter and editor at TechTarget. He received his B.A. in American Studies from Providence College and his M.A. in journalism from Northeastern University.