In a world where data is growing exponentially and the relationships between information are becoming increasingly complex, the traditional databases are no longer sufficient.
The course is designed for those who wish to deepen GQL (Graph Query Language) and understand how to use it effectively within modern graph database. During the lessons we will analyse the main graph database use cases, showing how this model overcomes the limitations of traditional databases when complex relationships between data need to be managed.
Why train on Graph Database and GQL?
- Immediate competitive advantagetechnology set to become market standard
- Up to 40% time saved in the analysis of complex data
- Enhances artificial intelligenceGQL and knowledge graph for generative AI
- Discover hidden patterns in the data, invisible to traditional approaches
- Accelerates strategic decisions with advanced analytics
The training course will clarify the differences between graphical database e graph database, illustrating when and why to adopt a node- and relationship-based approach. Through practical exercises you will learn how to write queries with Graph Query Language, understanding the logic behind the interrogation of the most commonly used graphs and patterns in the industry. The course is also an excellent basis for those who are looking for a DB design course oriented towards state-of-the-art technologies, providing concrete tools to model complex domains and develop scalable, high-performance solutions.
What will you learn in the our GQL database course:
- Fundamentals of graph database and language GQL
- Writing complex queries, analysing relationships and patterns
- Apply algorithms such as PageRank, Similarity, Louvain
- Building real patterns of transactions and fraud
- Approach to Graph AI and LLM integrated
Addressees and Requirements
The course is designed for those who wish to work with a graphical database, in particular using GQL (Graph Query Language), the emerging standard for querying the graph database in a simple and effective way.
- Recipients: developers, data engineers, analysts
- Prerequisites: basic knowledge of databases and query languages
- Methodtheory + exercises on real cases, with dedicated database