Cypher Aggregations

Who this course is for

This course is for developers, data engineers, and analysts who can already read and write basic CypheriFull definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. and want to summarise data rather than just retrieve it. If you find yourself exporting query results to another tool just to count, average, or rank them, this course shows you how to do that work directly in the database, in a single query. It is also useful preparation for anyone building reports, dashboards, or recommendation features on top of Neo4j. You should be comfortable with MATCH, WHERE, and RETURN from Cypher Fundamentals before you start, because every lesson builds aggregationiFull definition for aggregation (opens in a new tab)Grouping rows and computing a value over each group. In Cypher the grouping keys are whatever expressions in the same clause are not aggregated. on top of those clauses.

What you'll do

This is a hands-on course. You work in an embedded sandbox connected to a live Neo4j database loaded with the recommendations dataset: movies, the people who acted in and directed them, the users who rated them, and the genres that classify them. It is a realistic graph with enough data that aggregationiFull definition for aggregation (opens in a new tab)Grouping rows and computing a value over each group. In Cypher the grouping keys are whatever expressions in the same clause are not aggregated. results are meaningful, not toy numbers.

Every concept is paired with a query you run yourself, and each lesson is followed by a challenge that checks your answer against the graph. You collect values into lists with collect() and patterniFull definition for pattern (opens in a new tab)A graph structure written in Cypher, such as a node joined to another node by a relationship. comprehension, count nodesiFull definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties. and relationshipsiFull definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node., reshape and filter lists with functions such as size(), head(), and list comprehension, and calculate totals, averages, and percentiles of real ratings with sum(), avg(), min(), max(), and percentileCont(). You cannot pass a challenge by reading alone, so by the end you have proven you can write working aggregations, not just recognise them.

Where to go next

Working with Dates and Durations is the natural next step. Many of the values you aggregate in real projects are temporal — review dates, release years, career spans — and that course teaches you to convert, compare, and calculate with Neo4j's temporal types. The Neo4j Certified Professional exam tests aggregationiFull definition for aggregation (opens in a new tab)Grouping rows and computing a value over each group. In Cypher the grouping keys are whatever expressions in the same clause are not aggregated. alongside the rest of CypheriFull definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it., so the functions you practise here count directly toward a recognised, industry-standard credential.