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.

We all know we are at the peak of the hype cycle for…wait for it – Blockchain! We are also already aware of some of the benefits of blockchain - but can blockchain be applicable to traditional data management? Though real-world blockchain implementations in the enterprise are minimal so far, I do believe there is a ton of potential to solve some of the problems that businesses face.

New and Existing Applications Extend Five Year Partnership; Innovations Showcased at UN’s STI Forum 2018

Few industries have been revolutionized by big data as much as healthcare. In this episode, we talked about: Gene mapping, Creating new drugs, Real-time health data, Organ donation

A View from the Big Data & Analytics Retail Summit.

Have you ever thought about what the best charts are for visualizing distributions?

With increasing needs for data analytics and ever more stringent laws concerning data security and privacy (looking at you, GDPR), data governance has become a business imperative for any data-driven company. Master Data Management (MDM) is an essential part of any data governance strategy, it is commonly defined as the comprehensive method used to consistently define and manage the critical data of an organization to provide a single point of reference.

For the past few years, big data has been all the rage, but it has not delivered on all its promise. We were expecting omniscience at our fingertips, and we’re getting moderately well-targeted advertising instead. Don’t get confused though, big data is not going anywhere. On the contrary, data keeps growing at a dizzying rate, increasing in volume, variety, velocity, and veracity.

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.