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Cloudera Data Analyst Training for Apache Hadoop Course Overview

Cloudera Data Analyst Training for Apache Hadoop is a comprehensive course offered by Cloudera to help individuals gain the skills necessary to analyze large data sets with Apache Hadoop. This course is designed to help students learn the fundamentals of Apache Hadoop, from an introduction to the core components and concepts to the exciting world of real-time data analysis.
Students enrolled in this course will gain the ability to analyze large data sets with Apache Hadoop, Scala, and Crunch. The course covers topics from the basics of Hadoop to the configuration of the complex MapReduce system. Additionally, it covers topics related to the data processing lifecycle and managing Hadoop clusters.
Overall, this course provides the skills needed to become a proficient Hadoop data analyst. Students will gain the ability to analyze large data sets using Apache Hadoop and related technologies. Students enrolled in this course will also learn best practices and gain the skills necessary to query and manipulate large data sets. Ultimately, Cloudera Data Analyst Training for Apache Hadoop is an excellent course to gain the skills necessary to successfully process and analyze large data sets with Apache Hadoop.

The 1-on-1 Advantage

Get 1-on-1 session with our expert trainers at a date & time of your convenience.

Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.

4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.

Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Apache Hadoop Fundamentals
  • 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
  • What Is Hive?
  • What Is Impala?
  • Why Use Hive and Impala?
  • Schema and Data Storage
  • Comparing Hive and Impala to Traditional Databases
  • Use Cases
  • 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
  • Common Operators and Built-In Functions
  • Operators
  • Scalar Functions
  • Aggregate Functions
  • Data Storage
  • Creating Databases and Tables
  • Loading Data
  • Altering Databases and Tables
  • Simplifying Queries with Views
  • Storing Query Results
  • Partitioning Tables
  • Loading Data into Partitioned Tables
  • When to Use Partitioning
  • Choosing a File Format
  • Using Avro and Parquet File Formats
  • UNION and Joins
  • Handling NULL Values in Joins
  • Advanced Joins
  • Using Common Analytic Functions
  • Other Analytic Functions
  • Sliding Windows
  • Complex Data
  • Complex Data with Hive
  • Complex Data with Impala
  • Using Regular Expressions with Hive and Impala
  • Processing Text Data with SerDes in Hive
  • Sentiment Analysis and n-grams
  • Understanding Query Performance
  • Bucketing
  • Hive on Spark
  • How Impala Executes Queries
  • Improving Impala Performance
  • Custom SerDes and File Formats in Hive
  • Data Transformation with Custom Scripts in Hive
  • User-Defined Functions
  • Parameterized Queries
  • Comparing Hive, Impala, and Relational Databases
Live Online Training (Duration : 32 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

2000 + If you accept merging of other students. Per Participant & excluding VAT/GST
4 Hours
8 Hours
Week Days

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
1500 Per Participant & excluding VAT/GST
02 - 05 Oct
09:00 AM - 05:00 PM CST
(8 Hours/Day)
06 - 09 Nov
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites

• Basic knowledge of SQL and Linux
• A good understanding of databases and data modeling
• Hands-on experience with Big Data analytics tools
• Experience with Apache Hadoop, MapReduce, Apache Hive, Apache Pig, Apache Spark, and Apache Impala
• Knowledge and experience with scripting languages such as Java, Python, and Scala
• Ability to develop code in Hive, Pig, and Spark and debug/tune for performance
• Understanding of data warehousing and familiarity with SQL transformations

Target Audience

The target audience for Cloudera Data Analyst Training for Apache Hadoop training is typically individuals looking for a broad introduction to building data analysis solutions leveraging Apache Hadoop
This training is typically suitable for developers, system administrators, BI/ETL/DW professionals, and database administrators, as well as Testers, Architects, Data Analysts and other IT professionals looking to understand the principles of building data-intensive applications with Apache Hadoop
The training also covers the core components of Hadoop, including HDFS, MapReduce, YARN, Pig and Hive, and how to develop and debug Hadoop applications using these components
Additionally, the training will cover an introduction to Apache Spark and use cases, Apache HBase, Impala, and Sqoop
By the end of the training, participants will have the knowledge and confidence to leverage Apache Hadoop in their own data applications development

Learning Objectives of Cloudera Data Analyst Training for Apache Hadoop

1. Understand the fundamentals of Apache Hadoop and the Hadoop Distributed File System (HDFS).
2. Get hands-on training to implement Cloudera's powerful tools for extracting, transforming and loading data in Hadoop.
3. Learn how to use Hive to query data and Pig to process unstructured data in HDFS.
4. Gain the skills to create and optimize data storage with Sqoop, Flume and other Cloudera tools.
5. Get fluent in Apache HBase and Hadoop Architectures.
6. Learn how to optimize MapReduce queries with advanced tuning techniques.
7. Grasp big data ingestion and reporting techniques.
8. Understand how to use graphs for exploring data.
9. Get the ability to analyze data with Impala and Solr.
10. Utilize Reporting and Data Visualization with Hue.
11. Get an introduction to Apache Spark.
12. Get the skills to store and analyze data with Apache Kafka.
Student Name Feedback
Maurice Ndizeye
United States
A1. She is co-operative and has gd teaching methodology, she is kind
Pearlnath Joseph
United States
A2. Hospitality
Anantha Nagesh Etta
United States
A1. Good, knowledgeable
Deepak Hp
United States
A3. Am not sure.
Eleanor Downer
United States
A3. Maybe if there is a centre in Europe. I found the lectures quite long and dry - you don't remember much of the detail since we're rushing through the course quite quickly. I think it would help to have the majority of the sessions as hands-on-training and just a small amount of theory.
Suraj Hejmady Shenoy
United States
A3. For the right course, yes, I would consider coming back.
Sreeni Gangu
United States
A3. not likely
Jamey Lee
United States
A3. could be.
Debarshi Chatterjee
United States
A1. Abhishek is good with basic training concept and explaining concepts for the starters. one small recommendation - if he explains the concepts and not read from the slides he can save time to cover more topics and finish course on time.
Venu Kukkadapu
United States
A3. First weeks training premesis is not good, 2nd week is good.
Sibasis Das
United States
A3. Definitely
R Suneel Kumar
United States
A3. Yes
Murali Krishna Lakshmanakavi
United States
A3. yes
Karthikeyan Selvaraj
United States
A3. Yes
Abass Adebayo Gbadeyanka
United States
A3. Excellent performance


Yes, we do.
The Fee includes:
  • Testing Via Qubits
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1-on-1 you can select your own schedule, other students can be merged but you select the schedule. Choose 1-on-1 if published schedule do not meet your requirement. If you also want a private session, opt for 1-on-1 Private.
No, it is not included.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
You can request a refund if you do not wish to enroll in the course.
1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
Yes, you can pay from the course page and flexi page.
Yes, the site is secure by utilizing Secure Sockets Layer (SSL) Technology. SSL technology enables the encryption of sensitive information during online transactions. We use the highest assurance SSL/TLS certificate, which ensures that no unauthorized person can get to your sensitive payment data over the web.
We use the best standards in Internet security. Any data retained is not shared with third parties.
To receive an acknowledgment of your online payment, you should have a valid email address. At the point when you enter your name, Visa, and other data, you have the option of entering your email address. Would it be a good idea for you to decide to enter your email address, confirmation of your payment will be emailed to you.
After you submit your payment, you will land on the payment confirmation screen.It contains your payment confirmation message. You will likewise get a confirmation email after your transaction is submitted.
We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
Credit card transactions normally take 48 hours to settle. Approval is given right away; however,it takes 48 hours for the money to be moved.
Yes, we do accept partial payments, you may use one payment method for part of the transaction and another payment method for other parts of the transaction.
Yes, if we have an office in your city.
Yes, we do offer corporate training More details
Yes, we do.
Yes, we also offer weekend classes.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our @koenig-solutions.com email address.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the letter of course attendance post training completion via learning enhancement tool after registration.
Yes you can.
Yes, we do. For details go to flexi
You can pay through debit/credit card or bank wire transfer.
Yes you can request your customer experience manager for the same.
Yes, fee excludes local taxes.
Yes, Koenig Solutions is a Cloudera Learning Partner
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

Prices & Payments

Yes of course.
Yes, We are

Travel and Visa

Yes we do after your registration for course.

Food and Beverages



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“It is an interesting story and dates back half a century. My father started a manufacturing business in India in the 1960's for import substitute electromechanical components such as microswitches. German and Japanese goods were held in high esteem so he named his company Essen Deinki (Essen is a well known industrial town in Germany and Deinki is Japanese for electric company). His products were very good quality and the fact that they sounded German and Japanese also helped. He did quite well. In 1970s he branched out into electronic products and again looked for a German name. This time he chose Koenig, and Koenig Electronics was born. In 1990s after graduating from college I was looking for a name for my company and Koenig Solutions sounded just right. Initially we had marketed under the brand of Digital Equipment Corporation but DEC went out of business and we switched to the Koenig name. Koenig is difficult to pronounce and marketeers said it is not a good choice for a B2C brand. But it has proven lucky for us.” – Says Rohit Aggarwal (Founder and CEO - Koenig Solutions)
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