In my last blog post, I finished up how to create maps with your data using either point, area or flow representation. Today we’re starting with a new topic focusing in on how to visualize the distribution of data. You may remember from my “Mapping data to visualization usage” post that one way to break down the usage of chart is to divide them into these four groups: Comparison, Composition, Distribution and Relationship.
New and Existing Applications Extend Five Year Partnership; Innovations Showcased at UN’s STI Forum 2018
A View from the Big Data & Analytics Retail Summit.
Have you ever thought about what the best charts are for visualizing distributions?
Partnership to Accelerate Global City Network Access to Actionable Data to Address Climate Risks
In today’s blog post, we will give a light introduction to working with Neo4j’s query language, Cypher, as well as demonstrate how to get started with Neo4j on Google Cloud. You will learn how to quickly turn your Google BigQuery data or your Google Cloud logs into a graph data model, which you can use to reveal insights by connecting data points.
