The Value of Graph Analytics

By: Katana Graph

November 29, 2021

The Value of Graph Analytics

To understand the threats and opportunities, and to be competitive in today’s enterprise world, businesses must gather structured and unstructured data from all available sources.

Financial services, healthcare, pharmaceuticals, and telecoms rely on data and they accumulate vast amounts of it. The gathering of the data is a daunting task, and mining, query, and analysis require many resources. Even then the need for critical business decisions often necessitates analysis of billions of data points in a matter of minutes. Graph analytics is now an essential instrument for situations where the need for fast action mandates a need for fast analysis.

Elizabeth Wallace of RTInsights recently interviewed Farshid Sabet, Chief Business Officer at Katana Graph. Farshid summarizes the value of graph analytics.

“Graph analytics is used effectively in financial, security, health, and life sciences, and many more markets. Pharmaceutical companies use graph analytics and graph mining for various use cases, and they have employed teams of scientists to develop knowledge graphs to use data for faster drug discovery or more in-depth analysis.”

Farshid illustrates the extensive opportunities for knowledge graph use in the pharmaceutical industry. Knowledge graphs can connect up data from relevant chemical, biological, and clinical research, patient information, and medical journals, along with data about drug side effects and the genetic information of the patients and users.

There is a “tsunami of data coming, and yet there is a push for even faster time to insight.”

Before graph analytics, data was analyzed through batch modes on a periodic basis. This precluded many use cases where quick decisions rely on data analysis.

“For pharmaceuticals or drug discovery, there is a demand to shave time off clinical trials. Our goal is to allow faster analysis, flexibility in analyzing various unstructured data types, and to enable analysis of larger volumes of data.”

The goal of the Katana Graph Intelligence Platform is to make it possible for insights to be realized in real time. Farshid concludes that the value of graph analytics is changing and improving industries so that lives can be saved, fraud prevented, and new discoveries unleashed faster:

  • There are advanced innovations in graph analytics, mining, and AI within the pharmaceuticals market.
  • Pharmaceutical companies use graph analytics and graph mining for various use cases, and they have employed teams of scientists to develop knowledge graphs to use data for faster drug discovery and more in-depth analysis.
  • New tools are becoming available such as graph neural networks, which apply machine learning techniques to graph analytics.
  • Financial services are one of the big markets for graphs analytics and graph mining.
  • In telecom, some carriers are using graph analytics for spam detection and for providing more precise services to subscribers.

These business cases outline the importance of getting intelligence out of the data quickly and efficiently, giving the business time to take control of the opportunities and threats, and implement competitive advantages.

Competition has increased pressure for timely insights. Let Katana Graph ease the pressure. Let’s connect!

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