Hello. Welcome to the Graph Analytics module in the Big Data specialization. I'm Amarnath Gupta, a research scientist at the San Diego Supercomputer Center. What do I do research on? Well, a number of different areas, all generally related to data engineering. But the area I'm recently very excited about has to do with graphs. Now, graphs or networks has many people call them, are about studying relationships and relationship patterns on objects. I became interested in graphs when I was a graduate student and the professor in our artificial intelligence class showed us how a part of human knowledge can be represented as a kind of graphs called semantic networks. She showed us how even very simple things like relationships somewhere in a family can be represented and viewed as graphs. Represent your knowledge huh? Now, that got me really excited. Someday, I thought this will be a really interesting topic to research on. What I didn't realize then is that in just a few years graphs and the need to model and analyze them would become so dominant in both academia and industry that graphs will be found everywhere today. Now we look at Facebook, LinkedIn, Twitter, and many, many more companies that are thriving in the market with data that are represented, modeled, and processed as graphs. Now, even the entire World Wide Web, if you think about it, is a giant graph that people analyze. And that brings us to this course. Now, in this course, I'll introduce you to the wonderful world of Graph Analytics specifically, I'd like to show how different kinds of real world data science problems can be viewed and modeled as graphs. And how the process of solving them can apply analytical techniques that used graph based methods, that is Algorithms. This course would have four models. In model one, we'll introduce graphs and different applications that use graphs. In model two, we'll cover a number of common techniques, mathematical and algorithm techniques, that are used in Graph Analytics. In module three, we'll look at a graph database. And through some sort of a hands on guidance, we'll show you how to store and query graph data with the database. In module four, we'll cover some strategies of handling very large graphs and discuss how existing tools that are currently used by the community are actually prints. Thank you for joining this course and I sincerely hope that you'll find it both exciting and useful. Happy learning.