Course Description
The demand for Big Data professionals is increasing across the globe and it’s a great opportunity for the IT professionals to move into the most sought technology in the present day world. ExcelR offers classroom and instructor-led live online Big Data course with Hadoop, delivered by industry experts who are considered to be the best trainers in the industry. The training is studded with loads of practical assignments, case studies and project work, which ensures the hands-on experience for the participants. Our Big data training program is meticulously designed to become a professional Big data Hadoop developer and crack the job in the space of Big Data. Various tools like Sqoop, Hive, HBase, Scala, Spark, Spark streaming, Kafka are extensively covered as part of the training. Along with these several value added topics like SQL, AWS, Azure, Python, Linux etc are covered in the context of Bigdata Hadoop. All these topics are considered to be nice to have which complements BIg Data concepts and are sought after by the recruiters. Post training support is provided and necessary hand holding will be provided in terms of resume preparation, Interview questions etc. ExcelR’s Big data program is considered to be the best program in the industry owing to its comprehensive curriculum, hands on assignments and projects, top notch trainers with extensive Big Data experience and have passion for training. No wonder ExcelR’s Big Data course is considered to be the best in the industry.
Course Curriculum
- What is Big Data
- Need and significance of innovative technologies
- 3 Vs (Characteristics)
- Forms of Data & Sources
- Various Hadoop Distributions
- Significance of HDFS in Hadoop
- HDFS Features
- Daemons of Hadoop and functionalities
- Data Storage in HDFS
- Accessing HDFS
- Data Flow
- Hadoop Archives
- Introduction to MapReduce
- MapReduce Architecture
- MapReduce Programming Model
- MapReduce Algorithm and Phases
- Data Types
- Input Splits and Records
- Basic MapReduce Program
- Introduction to Apache Pig
- MapReduce Vs. Apache Pig
- SQL Vs. Apache Pig
- Different Data types in Apache Pig
- Modes of Execution in Apache Pig
- Execution Mechanism
- Data Processing Operators
- How to write a simple PIG Script
- UDFs in PIG
- The Metastore
- Comparison with Traditional Databases
- HiveQL
- Tables
- Querying Data
- User-Defined Functions
- Introduction to HBase
- HBase Vs HDFS
- Use Cases
- Basics Concepts
- HBase Architecture
- Zookeeper
- Clients
- MapReduce integration
- MapReduce over HBase
- Schema definition
- Basics of MySQL database
- Install and Configuration
- Load/Update/Delete – DML transactions on database
- Import and Export data
- Other MySQL functions
- Introduction to Sqoop
- Sqoop Architecture and Internals
- MySQL client and server installation
- How to connect relational database using Sqoop
- Sqoop Commands
- overview
- Installation
- The basic syntax
- Data types
- Programming practice
- Basics of Python
- Variables, expressions and statements
- Functions, Structures, Strings
- Strings and Files
- Basic visualizations
- Basic Statistics
- Spark Architecture (Eco System)
- SparkR setup
- Pyspark and Spark-Shell (scala) interfaces
- Spark SQL
- Spark MLLib
- Spark Streaming
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