Big Data Hadoop Analyst online training course helps you master Big Data Analysis using Hadoop, Pig and Hive. This course will enable an Analyst to work on Big Data and Hadoop which takes into consideration the burgeoning demands of the industry to process and analyze data at high speeds.
How the open source ecosystem of big data tools addresses challenges not met by traditional RDBMSs
Using Apache Hive and Apache Impala to provide SQL access to data
Hive and Impala syntax and data formats, including functions and subqueries
Create, modify, and delete tables, views, and databases; load data; and store results of queries
Create and use partitions and different file formats. Combining two or more datasets using JOIN or UNION, as appropriate
What analytic and windowing functions are, and how to use them. Store and query complex or nested data structures
Process and analyze semi-structured and unstructured data. Techniques for optimizing Hive and Impala queries
Extending the capabilities of Hive and Impala using parameters, custom file formats and SerDes, and external scripts
How to determine whether Hive, Impala, an RDBMS, or a mix of these is best for a given task
Requirements
A basic knowledge in any programming language is beneficial but not necessary.
Description
|| About Big Data Hadoop Analyst Training Course
BIT’s Big Data Hadoop Analyst online training course will enable an Analyst to work on Big Data and Hadoop which takes into consideration the burgeoning demands of the industry to process and analyze data at high speeds. This training course will give you the right skills to deploy various tools and techniques to be a Hadoop Analyst working with Big Data. Big Data Analyst offers a wide range of scope for the job seekers, data analytics is considered as a backbone of the company, thus, the employees handling the related department should have working knowledge on SQL or basic LINUX commands, the database, SQL, and query language for databases. The Big Data Hadoop Analyst Professional Program insights on installing, updating and maintaining MongoDB environment. Make them understand Data Volume, Data Evolution, Velocity of Data, MapReduce and the procedure of developing distributed processing of large data sets across clusters of computers and administering Hadoop
Big Data Analyst offers a wide range of scope for the job seekers, data analytics is considered as a backbone of the company, thus, the employees handling the related department should have working knowledge on SQL or basic LINUX commands, the database, SQL, and query language for databases. The Big Data Analyst Training insights on installing, updating and maintaining MongoDB environment. Make them understand Data Volume, Data Evolution, Velocity of Data, MapReduce and the procedure of developing distributed processing of large data sets across clusters of computers and administering Hadoop.
Course Content
Live Lecture
·The Motivation for Hadoop
·Hadoop Overview
·Data Storage: HDFS
·Distributed Data Processing: YARN, MapReduce, and Spark
·Data Processing and Analysis: Pig, Hive, and Impala
·Database Integration: Sqoop
·Other Hadoop Data Tools
·Exercise Scenario Explanation
·Practical Exercise
Live Lecture
·What Is Hive?
·What Is Impala?
·Why Use Hive and Impala?
·Schema and Data Storage
·Comparing Hive and Impala to Traditional Databases
·Use Cases
·Practical Exercise
Live Lecture
·Databases and Tables
·Basic Hive and Impala Query Language Syntax
·Data Types
·Using Hue to Execute Queries
·Using Beeline (Hive's Shell)
·Using the Impala Shell
·Practical Exercise
Live Lecture
·Operators
·Scalar Functions
·Aggregate Functions
·Practical Exercise
Live Lecture
·Creating Databases and Tables
·Loading Data
·Altering Databases and Tables
·Simplifying Queries with Views
·Storing Query Results
·Practical Exercise
Live Lecture
·Partitioning Tables
·Loading Data into Partitioned Tables
·When to Use Partitioning
·Choosing a File Format
·Using Avro and Parquet File Formats
·Practical Exercise
Live Lecture
·UNION and Joins
·Handling NULL Values in Joins
·Advanced Joins
·Practical Exercise
Live Lecture
·Using Common Analytic Functions
·Other Analytic Functions
·Sliding Windows
·Practical Exercise
Live Lecture
·Complex Data with Hive
·Complex Data with Impala
·Practical Exercise
Live Lecture
·Using Regular Expressions with Hive and Impala
·Processing Text Data with SerDes in Hive
·Sentiment Analysis and n-grams
·Practical Exercise
Live Lecture
·Understanding Query Performance
·Bucketing
·Hive on Spark
·Practical Exercise
Live Lecture
·How Impala Executes Queries
·Improving Impala Performance
·Practical Exercise
Live Lecture
·Custom SerDes and File Formats in Hive
·Data Transformation with Custom Scripts in Hive
·User-Defined Functions
·Parameterized Queries
·Practical Exercise
Live Lecture
·Comparing Hive, Impala, and Relational Databases
·Which to Choose?
·Conclusion
·Practical Exercise
Fees
Offline Training @ Vadodara
Classroom Based Training
Practical Based Training
No Cost EMI Option
5000045000
Online Training preferred
Live Virtual Classroom Training
1:1 Doubt Resolution Sessions
Recorded Live Lectures*
Flexible Schedule
4500035000
Corporate Training
Customized Learning
Onsite Based Corporate Training
Online Corporate Training
Certified Corporate Training
Certification
Upon the completion of the Classroom training, you will have an Offline exam that will help you prepare for the Professional certification exam and score top marks. The BIT Certification is awarded upon successfully completing an offline exam after reviewed by experts
Upon the completion of the training, you will have an online exam that will help you prepare for the Professional certification exam and score top marks. BIT Certification is awarded upon successfully completing an online exam after reviewed by experts.
This course is designed to clear Clouder Cetification Exam: CCA Data Analyst (CCA159))
