Graph Analytics for Big Data

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.*********Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following alo

Created by: Amarnath Gupta

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Overall Score : 78 / 100

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Course Description

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.

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Instructor Details

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Amarnath Gupta received his Ph.D. in Computer Science from Jadavpur University in India. He is currently a full Research Scientist at the San Diego Supercomputer Center of UC San Diego, and directs the Advanced Query Processing Lab. His primary areas of research include semantic information integration, large-scale graph databases, ontology management, event data management and query processing techniques. Before joining UC San Diego, he was the Chief Scientist at Virage, Inc., a startup company in multimedia information systems. Dr. Gupta has authored over 100 papers and a book on Event Modeling, holds 13 patents and is a recipient of the 2011 ACM Distinguished Scientist award.

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Reviews

3.9

160 total reviews

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By Sarah W on 5-Feb-18

Very interesting topic, but poor course. They totaly kill the oportunity to tech good things. Tools you need to accomplish are not working all the time and you need to search for the solution in discussion without knowing what are you looking for. I would appreciate whet they give at least some hint what to look for. It could be valuable. Than you just copy paste solution and do not knot what are you doing. I think deep knowledge what and why are you actually doing will be more valuable than cover every topic.

By Mike M on 17-May-17

not much explanation about the syntax of the commands given in excercises

By Roger S on 28-Jan-17

Really Thank you for all the big data course, just a little about the 5th course, Graph analytic, I think can must go to the deeper insight with more explanation, some of the modules was really vague!Thank you

By Pranas B on 26-Dec-17

I encountered numerous issues with the hands on exercises. Either copy paste errors or the VM simply hanging.

By Ankit S on 6-Sep-17

was not able to load the files in neo4j

By Nitish V on 9-Jul-18

The course theory was illustrated and demonstrated very well. Examples were shown and the lectures were short but concise. I appreciated this greatly. The professor also spoke very slowly and deliberately, so the viewers could understand and have time to let the information sink in. In contrast, although the guest lecturer for Neo4j was great, the material was not up-to-date and caused several issues in completing the assignment. Other students were able to lead the class in the right direction in order to even start the assignment. The GraphX on Cloudera virtual machine was almost impossible to replicate as well due to the material being so outdated. Week 5 of the course peaked my interest but lacked the resources to completely follow the instructions and understand the material that was being presented.

By Dauren B on 2-Mar-17

I like the content at a high level, and I have a better appreciation for the value of graph analytics. That being said, I struggled with the GraphX hands on exersizes, where many of the Scala commands simply hung.

By Reinaldo L N on 12-Sep-19

The last week had exercises run on a Linux VM and, different from the other courses, there were no instructions on installing Virtual Box and the Cloudera VM. I had to get the instructions at the forum, but they should be at the first week readings.

By Armando P on 10-Sep-19

Sorry but didnt see the point to this course as part of the overall specialization. Maybe as part of the "Load" in a ETL workflow but there would have been other options, better options. Felt it was just thrown in.

By Anton V on 14-Aug-17

Terrible. Did not understand most of the course. Badly explained. Manuals to software were not working. Shame, because it is a nice subject.

By John B on 2-Oct-17

Module 4 was absolutely pointless and terrible. The software was not easy to install and crucial instructions were missing. Additionally, the assignments required working with a dataset of size that was beyond the capabilities of most personal computers.

By Yaron K on 14-Aug-16

The material on graph analytics was of introductory level. A string of interesting ideas, with unclear explanations. The lesson on GraphX was basically a copy-paste introduction to it's abilities without actually teaching how to use it. The transcripts are full of mistakes. Someone not proficient in English or hard of hearing would be confused by them. It was somewhat difficult to understand the main lecturer. The best part was the explanation of Neo4j - and it was at an introductory level. A disappointment.