Big Data

• Understanding Big Data
• Evolution of Big Data
• Failure of Traditional Database in Handling Big Data
• 3 Vs of Big Data
• Sources of Big Data
• Different Types of Data
• Big Data Infrastructure
• Big Data Life Cycle
• Big Data Technology
• Big Data Applications
• Big Data Use Cases
• Cluster Computing
• Distribution Models
• Distributed File System
• Relational and Non‐Relational Databases
• Scaling Up and Scaling Out Storage
• Introduction to NoSQL
• Why NoSQL
• CAP Theorem
• ACID
• BASE
• Schemaless Databases
• NoSQL (Not Only SQL)
• Migrating from RDBMS to NoSQL

1 Laboratorio en vivo in this lesson — see the labs panel →

• Data Processing
• Shared Everything Architecture
• Shared‐Nothing Architecture
• Batch Processing
• Real‐Time Data Processing
• Parallel Computing
• Distributed Computing
• Big Data Virtualization
• Cloud Computing Types
• Cloud Services
• Cloud Storage
• Cloud Architecture

3 Laboratorio en vivo in this lesson — see the labs panel →

• Apache Hadoop
• Hadoop Storage
• Hadoop Computation
• Hadoop 2.0
• HBASE
• Apache Cassandra
• SQOOP
• Flume
• Apache Avro
• Apache Pig
• Apache Mahout
• Apache Oozie
• Apache Hive
• Hive Architecture
• Hadoop Distributions

• Terminology of Big Data Analytics
• Big Data Analytics
• Data Analytics Life Cycle
• Big Data Analytics Techniques
• Semantic Analysis
• Visual analysis
• Big Data Business Intelligence
• Big Data Real‐Time Analytics Processing
• Enterprise Data Warehouse
• Introduction to Machine Learning
• Machine Learning Use Cases
• Types of Machine Learning

• Itemset Mining
• Association Rules
• Frequent Itemset Generation
• Itemset Mining Algorithms
• Maximal and Closed Frequent Itemset
• Mining Maximal Frequent Itemsets: the GenMax Algorithm
• Mining Closed Frequent Itemsets: the Charm Algorithm
• CHARM Algorithm Implementation
• Data Mining Methods
• Prediction
• Important Terms Used in Bayesian Network
• Density-Based Clustering Algorithm
• DBSCAN
• Kernel Density Estimation
• Mining Data Streams
• Time Series Forecasting
• Clustering
• Distance Measurement Techniques
• Hierarchical Clustering
• Analysis of Protein Patterns in the Human Cancer‐Associated Liver
• Recognition Using Biometrics of Hands
• Expectation Maximization Clustering Algorithm
• Representative‐Based Clustering
• Methods of Determining the Number of Clusters
• Optimization Algorithm
• Choosing the Number of Clusters
• Bayesian Analysis of Mixtures
• Fuzzy Clustering
• Fuzzy C‐Means Clustering
• Big Data Visualization
• Conventional Data Visualization Techniques
• Tableau
• Bar Chart in Tableau
• Line Chart
• Pie Chart
• Bubble Chart
• Box Plot
• Tableau Use Cases
• Installing R and Getting Ready
• Data Structures in R
• Importing Data from a File
• Importing Data from a Delimited Text File
• Control Structures in R
• Basic Graphs in R

7 Laboratorio en vivo in this lesson — see the labs panel →