Details
Introduction
Use Cases
Data Analytics Proces
Data Preparation
Tools for Data Preparation
Data Preparation – Import/Export
PreProcessing
Data Analysis Introduction
Recommendation
Classification
Data Visualization using R
- Big Data Overview
- What is Big Data Analytics
- Necessity for Big Data Analytics
- Role of a Data Analyst
- What is Data Science
- Necessity for Data Science
- Role of Data Scientist
- Finance
- Retail
- Advertising
- Defense and Intelligence
- Telecommunications and Utilities
- Healthcare and Pharmaceuticals
- Preparation
- PreProcessing
- Analysis
- Post Processing
- Planning
- Data Collection
- Data Selection
- Introduction to SQL DB's
- Introduction to NoSql DB's
- Key / Value pair
- MongoDB
- Cassandra
- Graph DB's (Neo4j)
- Hands on Exercise : Using SQL and NoSql DB's
- Sqoop
- Flume
- Hands on Exercise : Usage of Tools
- Data Cleaning
- Data Filtering
- Data Completion
- Data Correction
- Data Standardization
- Data Transformation
- Tools for Data PreProcessing
- Data Preprocessing using Pig
- Writing Pig Latin scripts and processing data
- Data Preprocessing using Hive
- Writing Hive Scripts and processing data
- Hands on Exercise : Pig and Hive
- Sqoop
- Recommendation
- Classification
- Clustering
- Mahout
- Introduction to Recommendations
- Making recommendations, various techniques
- Hands on Exercise for Recommendations
- Classification System Overview
- Classification process
- Naive Bayes Classifier
- Decision Trees
- Examples of Classification
- Clustering
- Clustering basics
- Hierarchical clustering
- K-Means clustering
- Running clustering example
- Exploring distance measures
- Language basics
- Data Frames
- Vectorized operations on Data Frames
- Selection
- Projection
- Transformation
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