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This Week in Neo4j - 16th February 2019

Welcome to This Week in Neo4j, where we round up the last week in the world of graph databases. This week our Chief Scientist Dr Jim Webber describes how to run Neo4j in a Multi Data Center Environment, Max De Marzi shows us how to find the shortest path on a rail network, and Stefan Bieliauskas shows us why graphs are a perfect fit for modeling data provenance

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This Week in Neo4j - 16th February 2019

  1. 1. This Week in Neo4j 16th February 2019
  2. 2. Mark Needham Developer Relations Engineer at Neo4j / @markhneedham 2
  3. 3. The week's graph database news in one handy slide deck! Find the archive at
  4. 4. Featured Community: David Stevens Learn more about David
  5. 5. Jim Webber was back in the video studio, this time recording a video explaining how to run Neo4j in Multi Data Center Environments. Jim describes how to configure Neo4j servers with metadata to optimise the way that data is both queried and moved between them. Running Neo4j in Multi Data Center Environments Watch the video
  6. 6. Tomaz Bratanic shows how to use the Pearson Similarity algorithm to make sense of Kaggle’s Young People Survey dataset. This dataset contains music preferences, phobias, and health habits, and Tomaz shows how to use the algorithm to work out correlations between the answers in these different categories. Community detection of survey responses based on Pearson correlation coefficient with Neo4j Read the blog post
  7. 7. Versioning graphs is a commonly asked question, and Tom Geudens has started a series of post explaining the different approaches. Installment 1 focuses on time-based versioning of graphs. Using an e-commerce example, Tom shows how to separate identity from state, where the name of shops and the products that they sell can vary over time. Read the blog post Graph versioning Episode one — Time Based
  8. 8. Jennifer Reif‘s Marvel Series is back, and this week Jennifer shows us how to build the controller and service classes for handling requests and shaping results. Everything is now in place to feed the data into d3 to better visualize the Marvel Universe in the next installment! Create a Data Marvel — Part 8: Controlling and Servicing our Comic Endpoints Read the blog post
  9. 9. In his latest blog post, Max De Marzi explores a rail road dataset, showing how to load the data and make sense of it using shortest path algorithms. He also takes us through the code to write a procedure to find the shortest path based on total distance rather than number of cities. Calculating the best rail road paths in Neo4j Read the blog post
  10. 10. If you liked this check out the blog post This Week in Neo4j - 16th February 2019