Graph Analytics for Big Data

Module 1: Welcome to Graph Analytics

Welcome to Graph Analytics for Big Data

00:00

Module 2: Introduction to Graphs

2 readings

1 quiz

1 peer review

2 discussion prompts

Module 3: Graph Analytics

Focusing On Graph Analytics Techniques

00:00
Path Analytics

00:00
The Basic Path Analytics Question: What is the Best Path?

00:00
Inclusion and Exclusion Constraints

00:00
Connectivity Analytics

00:00
Disconnecting a Graph

00:00
Connectedness: Indegree and Outdegree

00:00
Community Analytics and Local Properties

00:00
Global Property: Modularity

00:00
Global Property: Modularity

00:00
Optional Lecture 1: Bi-directional Dijkstra Algorithm

00:00
Optional Lecture 2: Goal-directed Dijkstra Algorithm

00:00
Optional Lecture 3: Power Law Graphs

00:00
Optional Lecture 4: Measuring Graph Evolution

00:00
Optional Lecture 5: Eigenvector Centrality

00:00
Optional Lecture 6: Key Player Problems

00:00

3 readings

2 quizzes

2 discussion prompts

Module 4: Graph Analytics Techniques

Welcome to Graph Analytics Techniques

00:00
Hands-On: Downloading, Installing, and Running Neo4j

00:00
Hands-On: Getting Started With Neo4j

00:00
Hands-On: Modifying a Graph With Neo4j

00:00
Hands-On: Importing Data Into Neo4j

00:00
Hands-On: Basic Queries in Neo4j With Cypher – Part 1

00:00
Hands-On: Basic Queries in Neo4j With Cypher – Part 2

00:00
Hands-On: Path Analytics in Neo4j Using Cypher – Part 1

00:00
Hands-On: Path Analytics in Neo4j Using Cypher – Part 2

00:00
Hands-On: Connectivity Analytics in Neo4j With Cypher

00:00

12 readings

About the Supplementary Resources

00:00
Downloading, Installing, and Running Neo4j – Supplementary Resources

00:00
Getting Started With Neo4j – Supplementary Resources

00:00
Adding to and Modifying a Graph – Supplementary Resources

00:00
Download datasets used in this Graph Analytics with Neo4j

00:00
Importing Data Into Neo4j – Supplementary Resources

00:00
FAQ

00:00
Basic Queries in Neo4j With Cypher – Supplementary Resources

00:00
Path Analytics in Neo4j With Cypher – Supplementary Resources

00:00
Connectivity Analytics in Neo4j with Cypher – Supplementary Resources

00:00
Assignment: Practicing Graph Analytics in Neo4j With Cypher

00:00
Download All Neo4j Supplementary Resources (PDFs)

00:00

2 quizzes

Module 5: Computing Platforms for Graph Analytics

Introduction: Large Scale Graph Processing

00:00
A Parallel Programming Model for Graphs

00:00
Pregel: The System That Changed Graph Processing

00:00
Giraph and GraphX

00:00
Beyond Single Vertex Computation

00:00
Introduction to GraphX: Hands-On Demonstrations

00:00
Hands On: Building a Graph

00:00
Hands On: Building a Degree Histogram

00:00
Hands On: Plot the Degree Histogram

00:00
Hands On: Network Connectedness and Clustering Components

00:00
Hands On: Joining Graph Datasets

00:00

What Will You Learn?

Course Content

Module 1: Welcome to Graph Analytics

Welcome to Graph Analytics for Big Data

Module 2: Introduction to Graphs

What is a Graph?

Why Graphs?

Why Graphs? Example 1: Social Networking

Why Graphs? Example 2: Biological Networks

Why Graphs? Example 3: Human Information Network Analytics

Why Graphs? Example 4: Smart Cities

The Purpose of Analytics

What are the impact of Big Data’s V’s on Graphs?

2 readings

What to learn in this module

Download Slides for this Module

1 quiz

Introduction to Graphs

1 peer review

Graphs in Everyday Life

2 discussion prompts

Let’s Discuss: What else do you interact with that can be represented as a graph?

Optional: What’s the most interesting graph you reviewed?

Module 3: Graph Analytics

Focusing On Graph Analytics Techniques

Path Analytics

The Basic Path Analytics Question: What is the Best Path?

Inclusion and Exclusion Constraints

Connectivity Analytics

Disconnecting a Graph

Connectedness: Indegree and Outdegree

Community Analytics and Local Properties

Global Property: Modularity

Global Property: Modularity

Optional Lecture 1: Bi-directional Dijkstra Algorithm

Optional Lecture 2: Goal-directed Dijkstra Algorithm

Optional Lecture 3: Power Law Graphs

Optional Lecture 4: Measuring Graph Evolution

Optional Lecture 5: Eigenvector Centrality

Optional Lecture 6: Key Player Problems

3 readings

What to learn in this module

If this module takes a little longer… that’s OK!

Download All Slides for Module 3

2 quizzes

Graph Analytics Applications

Connectivity, Community, and Centrality Analytics

2 discussion prompts

Let’s Discuss: Where do you see path problems in your life?

Let’s Discuss: What kind of community analytics question would you like to ask?

Module 4: Graph Analytics Techniques

Welcome to Graph Analytics Techniques

Hands-On: Downloading, Installing, and Running Neo4j

Hands-On: Getting Started With Neo4j

Hands-On: Modifying a Graph With Neo4j

Hands-On: Importing Data Into Neo4j

Hands-On: Basic Queries in Neo4j With Cypher – Part 1

Hands-On: Basic Queries in Neo4j With Cypher – Part 2

Hands-On: Path Analytics in Neo4j Using Cypher – Part 1

Hands-On: Path Analytics in Neo4j Using Cypher – Part 2

Hands-On: Connectivity Analytics in Neo4j With Cypher

12 readings

About the Supplementary Resources

Downloading, Installing, and Running Neo4j – Supplementary Resources

Getting Started With Neo4j – Supplementary Resources

Adding to and Modifying a Graph – Supplementary Resources

Download datasets used in this Graph Analytics with Neo4j

Importing Data Into Neo4j – Supplementary Resources

FAQ

Basic Queries in Neo4j With Cypher – Supplementary Resources

Path Analytics in Neo4j With Cypher – Supplementary Resources

Connectivity Analytics in Neo4j with Cypher – Supplementary Resources

Assignment: Practicing Graph Analytics in Neo4j With Cypher

Download All Neo4j Supplementary Resources (PDFs)

2 quizzes

Quiz: Graph Analytics With Neo4j

Assessment Questions on ‘Practicing Graph Analytics in Neo4j With Cypher’

Module 5: Computing Platforms for Graph Analytics

Introduction: Large Scale Graph Processing

A Parallel Programming Model for Graphs