Top 9 emojis if you're, like, really into graphs


When you think of emojis, you may think of the popular ones first. For instance, there's the smiley faces, the hearts, the flame, and the ultra popular closed umbrella (). But what if you wanted to use emojis to just talk graphs with a fellow graph fan? Well you're in luck, because Apple had the foresight to include an array of graphs in their emoji selection; they're just a little hard to find! A bar graph has everything you love about graphs: bars, colors, and data.

A Compendium of Clean Graphs in R


When done right, graphs can be appealing, informative, and of considerable value to an academic article. We surmise that this is because researchers do not completely master their graphing software, and they are either too lazy or too busy to remedy the situation. Consequently, the produced graph is often a severe distortion of the ideal Platonian graph that the researcher had in mind initially.

Introducing a Graph-based Semantic Layer in Enterprises


Things, not Strings Entity-centric views on enterprise information and all kinds of data sources provide means to get a more meaningful picture about all sorts of business objects. This method of information processing is as relevant to customers, citizens, or patients as it is to knowledge workers like lawyers, doctors, or researchers. People actually do not search for documents, but rather for facts and other chunks of information to bundle them up to provide answers to concrete questions. Strings, or names for things are not the same as the things they refer to. Still, those two aspects of an entity get mixed up regularly to nurture the Babylonian language confusion.

Graph Analytics Using Big Data


Graphs are one of the most popular computer science concepts. They have been extensively used in real world applications be it a GPS on your phone or GPS device in your car that shows you the shortest path to your destination to a social network that suggests you friends that you can add to your list, graphs are everywhere. As the amount of data increases the concepts of graphs (breadth first search, Djikstra's etc.) all remain the same but the way the graphs are actually built changes. If you take the case of a social network, a particular person in a network can have hundreds of connections in his network and those connections might be further connected to hundreds of other users which may be physically in a different country altogether. Storing all this information in a typical relational database would not scale at all. Hence, we need specific technologies that cater to this scale of data and hence the usage of big data and big data system.

Knowledge Graphs: The Path to Enterprise AI - Neo4j Graph Database Platform


Michael Moore, Ph.D. is an Executive Director in the Advisory Services practice of Ernst & Young LLP. He is the National practice lead for Enterprise Knowledge Graphs AI in EY's Data and Analytics (DnA) Group. Moore helps EY clients deploy large-scale knowledge graphs using cutting-edge technologies, real-time architectures and advanced analytics. Omar Azhar is the Manager of EY Financial Services Organization Advisory – AI Strategy and Advanced Analytics COE at EY. Your email address will not be published.