Managing Big Data in Clusters and Cloud Storage by Cloudera via Coursera: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

Two prominent instructors, Ian Cook and Glynn Durham of the Cloudera institute offer the Managing Big Data in Clusters and Cloud Storage online course. The online course takes a total duration of 20 hours to complete and includes a verified certificate of completion. The course will be taught in English, however, the subtitles are available in nine different languages. The Managing Big Data in Clusters and Cloud Storage syllabus is an online-based five-week course and is provided as a part of the “Modern Big Data Analysis with SQL Specialization” programme. The Managing Big Data in Clusters and Cloud Storage by Coursera is a flexible beginner-level course that provides practical experience in SQL based engines such as Apache Impala and Apache Hive.

Course and certificate fees

The fees for the course Managing Big Data in Clusters and Cloud Storage is -

Head	Amount in INR
1 month	Rs. 4,115
3 month	Rs. 8,230
6 month	Rs. 12,345

certificate availability

Yes

certificate providing authority

Coursera

Eligibility criteria

Education

No prior educational programme is required to enroll and complete the coursework in the Managing Big Data in Clusters and Cloud Storage certification.

Certification Qualification Details

Students must be able to complete the necessary coursework, quizzes, and materials to earn the Managing Big Data in Clusters and Cloud Storage certification.

What you will learn

Knowledge of big data Knowledge of apache spark

The Managing Big Data in Clusters and Cloud Storage programme is planned for the following:

The Managing Big Data in Clusters and Cloud Storage certification syllabus will focus on how to handle large datasets, how to load them into clusters, and how to store them in the cloud.
The candidates will learn how to use different tools to search tables as well as existing databases in big data systems.
The candidates will learn how to employ different sets of tools for the purpose of exploring files in cloud storage and distributed big data file systems.
The candidates will become hands-on in Apache Hive and Apache Impala to build and handle big data databases and tables.
The candidates will be able to define and select from different data types and file formats for big data systems.

The syllabus

Module 1: Orientation to Data in Clusters and Cloud Storage

Videos

Welcome to the Course
Browsing Tables with Hue
Browsing Tables with SQL Utility Statements
Browsing HDFS with the Hue File Browser
Browsing HDFS from the Command Line
Understanding S3 and Other Cloud Storage Platforms
Browsing S3 Buckets from the Command Line

Readings

Review and Preparation
Instructions for Downloading and Installing the Exercise Environment
Troubleshooting the VM

Assignment

Week 1 Graded Quiz

Discussion Prompt

Introduce Yourself

Module 2: Defining Databases, Tables, and Columns

Videos

Week 2 Introduction
Introduction to the CREATE TABLE Statement
Using Different Schemas on the Same Data
Specifying TBLPROPERTIES
Examining, Modifying, and Removing Tables
Hive and Impala Interoperability
Impala Metadata Refresh

Readings

Creating Databases and Tables with Hue
Creating Databases and Tables with SQL
Permissions to Create Databases and Tables
The ROW FORMAT Clause
The STORED AS Clause
The LOCATION Clause
CREATE TABLE Shortcuts
Using Hive SerDes
Working with Unstructured and Semi-Structured Data
Examining Table Structure
Dropping Databases and Tables
Modifying Existing Tables

Assignment

Week 2 Practice Quiz
Week 2 Graded Quiz

Discussion Prompt

Most Difficult to Understand

Module 3: Data Types and File Types

Videos

Week 3 Introduction
Overview of Data Types
Choosing the Right Data Types
Overview of File Types
Choosing the Right File Types

Readings

Integer Data Types
Decimal Data Types
Character String Data Types
Other Data Types
Examining Data Types
Out-of-Range Values
Text Files
Avro Files
Parquet Files
ORC Files
Other File Types
Creating Tables with Avro and Parquet Files

Assignment

Week 3 Practice Quiz
Week 3 Graded Quiz

Discussion Prompt

What's Your Type

Module 4: Managing Datasets in Clusters and Cloud Storage

Videos

Week 4 Introduction
Refresh Impala's Metadata Cache after Loading Data
Loading Files into HDFS with Hue's Table Browser
Loading Files into HDFS with Hue's File Browser
Loading Files into HDFS from the Command Line
Loading Files into S3 from the Command Line
Using Hive and Impala to Load Data into Tables
Conclusion

Readings

More about HDFS Shell Commands
Chaining and Scripting with HDFS Commands
HDFS Permissions
Other Ways to Load Files into S3
S3 Permissions
Missing Values
Character Sets
Using Sqoop to Import Data
More Sqoop Import Options
Using Sqoop to Export Data
SQL LOAD DATA Statements
SQL INSERT Statements
SQL INSERT ... SELECT and CTAS Statements

Assignments

Week 4 Practice Quiz
Week 4 Graded Quiz

Peer Review

Data Management

Discussion Prompt

Get a Load of This

Module 5: Optimizing Hive and Impala (Honors)

Videos

Week 5 Introduction
What to Do When Queries Are Too Complex
What to Do When Queries Take Too Long
When to Use Table Partitioning
When to Use Complex Columns
File Systems versus Storage Engines

Readings

Creating and Querying Views
Modifying and Removing Views
Materialized and Non-Materialized Views
The ORDER BY Clause in Views
Choosing Which Query Engine to Use
Understanding Map Tasks and Reduce Tasks
Hive Query Performance Patterns
Understanding Execution Plans
Table and Column Statistics
Other Strategies for Query Optimization
Creating Partitioned Tables
Loading Data with Dynamic Partition
Loading Data with Static Partitioning
Risks of Using Partitioning
Complex Data Types
Creating Tables with Complex Data
Querying Complex Data with Hive
Querying Complex Data with Impala
Complex Data in Practice
Overview of Apache Kudu

Assignments

Week 5 Practice Quiz
Week 5 Graded Quiz

Discussion Prompt

Questions?

Admission details

Filling the form

To enroll in the Managing Big Data in Clusters and Cloud Storage online course and earn a verified certificate, follow the steps outlined below.

Step 1: The applicant can go to the website listed to initiate an application for the programme.

Step 2: After selecting "Enroll" from the menu, students must click "Next."

Step 3: The applicant must then fill out and submit the registration or application form, which must have all relevant material.

Step 4: Before enrolling in the course, students must first pay the course fee.

Scholarship Details

Coursera will provide financial assistance to students who cannot afford to cover the course fee. Candidates may qualify for financial assistance by using the drop-down menu to the left of the "Enroll" tab and clicking "Financial Aid." After the applications have been submitted, the approved applicants will be notified.

How it helps

Managing Big Data in Clusters and Cloud Storage certification benefits the candidates starting at a beginner level of learning with flexible based coursework in the area of Big Data and SQL. Candidates will be able to hone their skills and run queries through SQL engines. The candidate's abilities would allow him or her to carve out a promising future in big data analytics and SQL and build his or her career in the world of big data as a confident candidate with hands-on tools and experience.

Ian Cook and Glynn Durham from the Cloudera institute offer the coursework, signs, approves, and authenticates the certification, making it an internationally recognised certificate. With such a credential, an applicant would be able to communicate with potential employers and recruiters in online professional networking portals such as Linkedin. For any future project partnership, the applicant would be willing to partner with like-minded colleagues or experts. Furthermore, the applicant will be more likely to be hired in specialised roles requiring knowledge of SQL engines and big data implementation.

Instructors

Mr Glynn Durham
Senior Instructor
Cloudera

Other Masters

Mr Ian Cook
Staff Curriculum Developer
Cloudera

FAQs

What are the benefits of choosing the trial option available in this course?

Yes, candidates who apply for the Managing Big Data in Clusters and Cloud Storage training programme can attend the programme for one week for free.

What is the advantage of flexible coursework offered?

In a self-paced learning environment, Managing Big Data in Clusters and Cloud Storage benefits the candidate because they can learn at their pace without following a rigid schedule.

What are the system requirements required for the students to possess for this coursework?

The system requirements are - 64-bit OS type, Windows or macOS, or Linux, 25GB free disk space, 8 GB RAM or higher, Windows XP, AMD-V or Intel VT-x virtualization, and 7-Zip or WinZip.

What is the procedure to register for the course?

Applicants need to visit the official website to register for the programme and submit the application

How can the course completion certificate benefit my career prospects?

Managing Big Data in Clusters and Cloud Storage online course as a verified credential can be added to a candidate's profile, resume, or CV, as well as shared on social media.

Are subtitles available for students who are not comfortable with English?

Subtitles in nine languages are given to help the candidate's learning since the course is solely taught in English.

How long does this certificate programme last?

The coursework will be completely done online which will take a total of 20 hours to complete.

Are there any prerequisites for applicants to be considered, such as prior programming or experience?

The applicant does not require any special credentials to apply for and learn about the Managing Big Data in Clusters and Cloud Storage certification.

Is there any provision for financial assistance?

Yes, to obtain financial aid for the Managing Big Data in Clusters and Cloud Storage certificate, students must apply for the "Financial Assistance" option after choosing the "Enroll" option on the website page.