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The power of Manchester City: a data analysis

What makes Manchester City such a great team? The infographic below illustrates one of the teams most powerful characteristics: its successful passing capability. The visualisation is based upon the Opta dataset released in August 2011, containing the high detailed Bolton vs Manchester City match statistics. The data has been loaded in the neo4j graph databases

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Coalition-Cocktail – Hacking the Elections @ Engagor

Last weekend, Engagor organised their hacktheelections hackaton. The Datablend team (Quentin, Stijn and Davy) was joined by Marc Broos, Tim Coene and Josbert van de Zande with one goal in mind: trying to visualise the (pre-arranged?) political coalition and, if possible, also predict the formation-period. Technically, we extracted over 160K tweets through the Engagor API.

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Yelp graph: checkin-based business clustering

Recently, Yelp made available a sample dataset from the greater Phoenix metropolitan area including around 11.000 business, 8000 checkin-sets, 43.000 users and 230.000 user reviews. With the help of this data, data scientists can execute real-life experiments with various data mining/machine learning algorithms. In our case, we are interested in finding out whether it is possible

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Graphs, Graphs, Graphs, …

Last week, Datablend open-sourced two new Tinkerpop Blueprints implementations: blueprints-mongodb-graph and blueprints-datomic-graph. Tinkerpop is an open source project that provides an entire stack of technologies within the Graph Database space. At the core of this stack is the Blueprints framework. Blueprints can be considered as the JDBC of Graph Databases. By providing a collection of

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