Graphtopia : Navigating the Data Landscape

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Attended the 2nd graph database event - "Graphtopia : Navigating the Data Landscape" at Microsoft Reactor, Bengaluru on 11th February 2023.

Had an amazing time at the knowledge-sharing event hosted by Siddhant Agarwal. It was great to hear about various topics from different speakers with admirable experience & knowledge. 


I would like to thank all the speakers for enlightening about various concepts relating to graph database, Data platform, AI-ML & cloud.

Siddhant Agarwal hosted this amazing event and shared some amazing use-cases and examples of graph databases & especially about Neo4j. He explained the importance of graph databases, use-cases, examples, working, etc. in the first meetup and he carried it forward by walking through the practical use of the Cypher queries in the Neo4j sandbox. Keeping in mind the audiences' familiarity with the concept of graph databases and also the awareness about Neo4j, he tried commendably well to take the audience from the stage of being unaware about the topic to practically using it on the go. He managed to optimally utilize the given time frame of the session to enlighten the audience about the concept as well as nicely briefed about the practical aspects of it. Its always great to hear him speak about various topics and concepts. It was an amazingly informative session.

Shubham M. nicely elucidated about the detection of fraudulent collision patterns using graphs as well as he explained about the importance of using graph databases for a given use case of anomaly detection. He illustrated that in today's data driven world, any company produces millions of data points and hence fraud detection is the need of the hour. Graph databases allows easy visual pattern recognition to form investigative/audit questions. Some particular type of anomalies can only be detected using graph databases. He also touched upon the concepts of Louvain algorithm, PageRank algorithm etc. It was a great session which provided vast amount of knowledge and points to research about.


Jitendra Shah threw light upon the topics of data platform, data warehouse, data lake, lakehouse, data mesh, etc. He also explained these concepts and also described about their importance as well as the differences in their use-cases. He enlightened about the concept of data democratization and touched upon the topics of data platform on cloud. It was a wonderful session which helped to co-relate and learn about different topics required in the field of data engineering, cloud & AI-ML. 

Vishwas Narayan nicely explained about graph native machine learning. He described about the use cases of graphs in machine learning. It was a good knowledge-sharing session.


All the sessions were really informative and insightful. Special thanks to Siddhant Agarwal, Parth Varu, Rashmita Bhowmick & Microsoft for organizing this wonderful event.

Looking forward to attend more events by Neo4j in future.




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