Workshop - Graph analytics and graph databases in Python

Hi All,

We are excited to invite you to another informative and coding Saturday morning.

The understanding of complex relationships and interdependencies between different data points is crucial to many decision-making processes.

Graph analytics have found their way into every major industry, from marketing and financial services to transportation. Fraud detection, recommendation engines, and process optimization are some of the use cases where real-time decisions are mission-critical, and the underlying domain can be easily modeled as a graph. When it comes to complex networks, it’s often necessary to perform graph algorithms such as calculating PageRank, identifying communities, traversing relationships, etc. Memgraph is a stream processing platform powered by an in-memory graph database that can be used to analyze graph-based data models.

Graph analytics can provide insights into complex networks that would otherwise require resource-intensive computations. It is also much simpler to store data in the form of graphs, as the graph model doesn't rely on predefined and rigid tables. This data can then be traversed and analyzed using the Cypher query language without having to implement custom algorithms or relying on development-heavy solutions.

We will demonstrate how easy it is to work with graph databases in Python using the open-source library GQLAlchemy. GQLAlchemy is an OGM (Object Graph Mapper) that can be used to:
· Connect to a graph database
· Create nodes and relationships as classes in Python
· Load data from the database
· Run graph algorithms
· Define a graph schema model and validator

We will cover these and other concepts through a simple workshop so you can gain a basic understanding of graph analytics in Python and how to get the most out of your data.

Bio:
Ivan Despot is a Developer Relations Engineer at Memgraph. His passion for mathematics and graph theory inspired him to become part of the Memgraph team and start contributing to the field of graph analytics. Besides graph-based technologies, he is also interested in streaming platforms, stream processing and event-driven development.

Twitter:[ https://twitter.com/ivan_g_despot](https://twitter.com/ivan_g_despot)
LinkedIn:[ https://www.linkedin.com/in/ivan-g-despot/](https://www.linkedin.com/in/ivan-g-despot/)
Medium:[ https://gdespot.medium.com/](https://gdespot.medium.com/)

Let Roman Golovnya know if you are keen to present at future events. You can contact him via meetup messages or email roman.golovnya@gmail.com.