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Big Data Architect Master's Course

221 Ratings

Our Big Data Architect master's course lets you gain proficiency in Big Data. You will work on real-world projects in Hadoop Development, Hadoop Administration, Hadoop Analysis, Hadoop Testing, Spark, Python, Splunk Developer and Admin, Apache Storm, NoSQL databases and more. In this program, you will cover 13 courses and 33 industry-based projects. As a part of this online classroom training, you will receive four additional self-paced courses co-created with IBM, namely, Spark MLlib, and Python for Data Science.

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13+
Courses
33+
Projects
277
Hours
  • Self Paced Training
    • Course 1
      Big Data Hadoop & Spark

    • Course 2
      Apache Spark & Scala

    • Course 3
      Splunk Developer & Admin

    • Course 4
      Python for Data Science

    • Course 5
      MongoDB

    • Course 6
      AWS Big Data

    • Course 7
      Hadoop Testing 

    • Course 8
      Apache Storm 

    • Course 9
      Apache Kafka 

    • Course 10
      Pyspark

    • Course 11
      Apache Cassandra 

    • Course 12
      Java 

    • Course 13
      Linux 

Key Highlights

205 Hrs Instructor Led Training
277 Hrs Self-paced Videos
384 Hrs Project & Exercises
Certification
Job Assistance
Flexible Schedule
Lifetime Free Upgrade
Mentor Support
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Big Data Architect Overview

List of Courses Included:

Self-paced Courses:

  • Big Data Hadoop and Spark
  • Apache Spark and Scala
  • Splunk Developer and Admin
  • Python for Data Science
  • MongoDB
  • AWS Big Data
  • Hadoop Testing
  • Apache Storm
  • Apache Kafka
  • Pyspark Training
  • Apache Cassandra
  • Java
  • Linux
  • Introduction to Hadoop ecosystem
  • Working with HDFS and MapReduce
  • Real-time analytics with Apache Spark
  • ETL in Business Intelligence domain
  • Working on large amounts of data with NoSQL databases
  • Real-time message brokering system
  • Hadoop analysis and testing

There are no prerequisites for taking up this training program.

  • Global Hadoop market to reach $84.6 billion in 2 years – Allied Market Research
  • The number of jobs for all US-based data professionals will increase 2.7 million per year – IBM
  • A Hadoop Administrator in the US can get a salary of $123,000 – Indeed

Big Data is the fastest growing and the most promising technology that aids profiles like Big Data Engineer and Big Data Solutions Architect that are in huge demand. This Big Data Architect master’s course will help you grab the best jobs in this domain.

This Intellipaat training program has been specifically created to let you master the Hadoop architecture, along with helping you gain proficiency in Business Intelligence domain. Upon the completion of the training, you will be well-versed in extracting valuable business insights from raw data. This way, you can apply for top jobs in the Big Data ecosystem.

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Who Can Apply for the Course?

  • Data Science Professionals
  • Business Intelligence Professionals
  • Big Data Professionals aiming to upskill themselves 
  • Software Developers
  • Information Architects
  • Individuals aspiring to build a career as a Big Data Architect
  • Freshers and Undergraduates can apply for the course as well
Who can apply

What roles does a Big Data Architect play?

Applications Architect

Help clients make changes and transformations in their organization by solving complex problems.

Information Architect

Implement large-scale data warehouses or data lakes on the cloud with the help of AWS Native and other similar services.

Data Analyst

Create solutions using the data warehouse systems, like IICS, Airflow, and Snowflake.

Big Data Developer

Design and create data ingestion pipelines and also perform conversion activities and data migration.

Big Data Architect

Adopt leading technologies in the industry to get high-performance computation in the organization, along with the required data storage solutions.

Senior Data Architect

Simplify the flow of data and eliminate unrelated costs of fragmented and complicated data systems of the organization

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Skills to Master

Hadoop

HDFS

MapReduce

Spark

Scala

Splunk

Mapping

Pivots

Python

Statistics

Data Science with Python

Machine Learning

PySpark

Lambda functions

MongoDB

Apache Kafka

Apache Storm

ETL

Hive

AWS Big Data

Hadoop Testing

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Tools to Master

hadoop AWS spark scala splunk python pyspark hive apache-pig mapreduce sqoop mongodb storm kafka cassandra java linux
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Curriculum

Live Course Self Paced

Module 01 – Hadoop Installation and Setup
Module 02 – Introduction to Big Data Hadoop and Understanding HDFS and MapReduce
Module 03 – Deep Dive in MapReduce
Module 04 – Introduction to Hive
Module 05 – Advanced Hive and Impala
Module 06 – Introduction to Pig
Module 07 – Flume, Sqoop and HBase
Module 08 – Writing Spark Applications Using Scala
Module 09 – Use Case Bobsrockets Package
Module 10 – Introduction to Spark
Module 11 – Spark Basics
Module 12 – Working with RDDs in Spark
Module 13 – Aggregating Data with Pair RDDs
Module 14 – Writing and Deploying Spark Applications
Module 15 – Project Solution Discussion and Cloudera Certification Tips and Tricks
Module 16 – Parallel Processing
Module 17 – Spark RDD Persistence
Module 18 – Spark MLlib
Module 19 – Integrating Apache Flume and Apache Kafka
Module 20 – Spark Streaming
Module 21 – Improving Spark Performance
Module 22 – Spark SQL and Data Frames
Module 23 – Scheduling/Partitioning

Following topics will be available only in self-paced mode:

Module 24 – Hadoop Administration – Multi-node Cluster Setup Using Amazon EC2
Module 25 – Hadoop Administration – Cluster Configuration
Module 26 – Hadoop Administration – Maintenance, Monitoring and Troubleshooting
Module 27 – ETL Connectivity with Hadoop Ecosystem (Self-Paced)
Module 28 – Hadoop Application Testing
Module 29 – Roles and Responsibilities of Hadoop Testing Professional
Module 30 – Framework Called MRUnit for Testing of MapReduce Programs
Module 31 – Unit Testing
Module 32 – Test Execution
Module 33 – Test Plan Strategy and Writing Test Cases for Testing Hadoop Application

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Tools covered

Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered

Scala Course Content

Module 01 – Introduction to Scala
Module 02 – Pattern Matching
Module 03 – Executing the Scala Code
Module 04 – Classes Concept in Scala
Module 05 – Case Classes and Pattern Matching
Module 06 – Concepts of Traits with Example
Module 07 – Scala–Java Interoperability
Module 08 – Scala Collections
Module 09 – Mutable Collections Vs. Immutable Collections
Module 10 – Use Case Bobsrockets Package

Spark Course Content

Module 11 – Introduction to Spark
Module 12 – Spark Basics
Module 13 – Working with RDDs in Spark
Module 14 – Aggregating Data with Pair RDDs
Module 15 – Writing and Deploying Spark Applications
Module 16 – Parallel Processing
Module 17 – Spark RDD Persistence
Module 18 – Spark MLlib
Module 19 – Integrating Apache Flume and Apache Kafka
Module 20 – Spark Streaming
Module 21 – Improving Spark Performance
Module 22 – Spark SQL and Data Frames
Module 23 – Scheduling/Partitioning

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Tools covered

Tools Covered Tools Covered

Module 1 – Splunk Development Concepts
Module 2 – Basic Searching
Module 3 – Using Fields in Searches
Module 4 – Saving and Scheduling Searches
Module 5 – Creating Alerts
Module 6 – Scheduled Reports
Module 7 – Tags and Event Types
Module 8 – Creating and Using Macros
Module 9 – Workflow
Module 10 – Splunk Search Commands
Module 11 – Transforming Commands
Module 12 – Reporting Commands
Module 13 – Mapping and Single Value Commands
Module 14 – Splunk Reports and Visualizations
Module 15 – Analyzing, Calculating and Formatting Results
Module 16 – Correlating Events
Module 17 – Enriching Data with Lookups
Module 18 – Creating Reports and Dashboards
Module 19 – Getting Started with Parsing
Module 20 – Using Pivot
Module 21 – Common Information Model (CIM) Add-On

Splunk Administration Topics

Module 22 – Overview of Splunk
Module 23 – Splunk Installation
Module 24 – Splunk Installation in Linux
Module 25 – Distributed Management Console
Module 26 – Introduction to Splunk App
Module 27 – Splunk Indexes and Users
Module 28 – Splunk Configuration Files
Module 29 – Splunk Deployment Management
Module 30 – Splunk Indexes
Module 31 – User Roles and Authentication
Module 32 – Splunk Administration Environment
Module 33 – Basic Production Environment
Module 34 – Splunk Search Engine
Module 35 – Various Splunk Input Methods
Module 36 – Splunk User and Index Management
Module 37 – Machine Data Parsing
Module 38 – Search Scaling and Monitoring
Module 39 – Splunk Cluster Implementation

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Tools covered

Tools Covered

Module 01 – Introduction to Data Science using Python
Module 02 – Python basic constructs
Module 03 – Maths for DS-Statistics & Probability
Module 04 – OOPs in Python (Self paced)
Module 05 – NumPy for mathematical computing
Module 06 – SciPy for scientific computing
Module 07 – Data manipulation
Module 08 – Data visualization with Matplotlib
Module 09 – Machine Learning using Python
Module 10 – Supervised learning
Module 11 – Unsupervised Learning
Module 12 – Python integration with Spark (Self paced)
Module 13 – Dimensionality Reduction
Module 14 – Time Series Forecasting

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Tools covered

Tools Covered

Module 01 – Introduction to NoSQL and MongoDB
Module 02 – MongoDB Installation
Module 03 – Importance of NoSQL
Module 04 – CRUD Operations
Module 05 – Data Modeling and Schema Design
Module 06 – Data Management and Administration
Module 07 – Data Indexing and Aggregation
Module 08 – MongoDB Security
Module 09 – Working with Unstructured Data

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Tools covered

Tools Covered

Module 01 – Introduction to Big Data and Data Collection
Module 02 – Introduction to Cloud Computing & AWS
Module 03 – Elastic Compute and Storage Volumes
Module 04 – Virtual Private Cloud
Module 05 – Storage – Simple Storage Service (S3)
Module 06 – Databases and In-Memory DataStores
Module 07 – Data Storage
Module 08 – Data Processing
Module 09 – Data Analysis
Module 09 – Data Visualization and Data Security

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Tools covered

Tools Covered

Module 01 – Introduction to Hadoop and Its Ecosystem, MapReduce and HDFS
Module 02 – MapReduce
Module 03 – Introduction to Pig and Its Features
Module 04 – Introduction to Hive
Module 05 – Hadoop Stack Integration Testing
Module 06 – Roles and Responsibilities of Hadoop Testing
Module 07 – Framework Called MRUnit for Testing of MapReduce Programs
Module 08 – Unit Testing
Module 09 – Test Execution of Hadoop: Customized
Module 10 – Test Plan Strategy Test Cases of Hadoop Testing

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Tools covered

Tools Covered

Module 01 – Understanding the Architecture of Storm
Module 02 – Installation of Apache Storm
Module 03 – Introduction to Apache Storm
Module 04 – Apache Kafka Installation
Module 05 – Apache Storm Advanced
Module 06 – Storm Topology
Module 07 – Overview of Trident
Module 08 – Storm Components and Classes
Module 09 – Cassandra Introduction
Module 10 – Boot Stripping

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Tools covered

Tools Covered

Module 01 – What is Kafka – An Introduction
Module 02 – Multi Broker Kafka Implementation
Module 03 – Multi Node Cluster Setup
Module 04 – Integrate Flume with Kafka
Module 05 – Kafka API
Module 06 – Producers & Consumers

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Tools covered

Tools Covered

Module 01 – Introduction to the Basics of Python
Module 02 – Sequence and File Operations
Module 03 – Functions, Sorting, Errors and Exception, Regular Expressions, and Packages
Module 04 – Python: An OOP Implementation
Module 05 – Debugging and Databases
Module 06 – Introduction to Big Data and Apache Spark
Module 07 – Python for Spark
Module 08 – Python for Spark: Functional and Object-Oriented Model
Module 09 – Apache Spark Framework and RDDs
Module 10 – PySpark SQL and Data Frames
Module 11 – Apache Kafka and Flume
Module 12 – PySpark Streaming
Module 13 – Introduction to PySpark Machine Learning

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Tools covered

Tools Covered Tools Covered

Module 01 – Advantages and Usage of Cassandra
Module 02 – CAP Theorem and No SQL DataBase
Module 03 – Cassandra fundamentals, Data model, Installation and setup
Module 04 – Cassandra Configuration
Module 05 – Summarization, node tool commands, cluster, Indexes, Cassandra & MapReduce, Installing Ops-center
Module 06 – Multi Cluster setup
Module 07 – Thrift/Avro/Json/Hector Client
Module 08 – Datastax installation part,· Secondary index
Module 09 – Advance Modelling
Module 10 – Deploying the IDE for Cassandra applications
Module 11 – Cassandra Administration
Module 12 – Cassandra API and Summarization and Thrift

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Tools covered

Tools Covered

Module 01 – Core Java Concepts
Module 02 – Writing Java Programs using Java Principles
Module 03 – Language Conceptuals
Module 04 – Operating with Java Statements
Module 05 – Concept of Objects and Classes
Module 06 – Introduction to Core Classes
Module 07 – Inheritance in Java
Module 08 – Exception Handling in Detail
Module 09 – Getting started with Interfaces and Abstract Classes
Module 10 – Overview of Nested Classes
Module 11 – Getting started with Java Threads
Module 12 – Overview of Java Collections
Module 13 – Understanding JDBC
Module 14 – Java Generics
Module 15 – Input/Output in Java
Module 16 – Getting started with Java Annotations
Module 17 – Reflection and its Usage

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Tools covered

Tools Covered

Module 01 – Introduction to Linux
Module 02 – File Management
Module 03 – Files and Processes
Module 04 – Introduction to Shell Scripting
Module 05 – Conditional, Looping statements and Functions
Module 06 – Text Processing
Module 07 – Scheduling Tasks
Module 08 – Advanced Shell Scripting
Module 09 – Database Connectivity
Module 10 – Linux Networking

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Tools covered

Tools Covered
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Project Work

Projects will be a part of your Big Data Master’s program to consolidate your learning. It will ensure that you have real-world experience in Big Data.

Career Transition

55% Average Salary Hike

$1,16,000 Highest Salary

11000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Big Data Architect Certification

This Big Data Architect course is created in collaboration with IBM to help you get into top organizations. Here, you will work on various real-world projects, assignments, and case studies which will enhance your skills in Big Data and fast-track your career in this domain.

This is a comprehensive course that is designed to clear multiple certifications such as:

  • CCA Spark and Hadoop Developer (CCA175)
  • Splunk Certified Power User Certification
  • Splunk Certified Admin Certification
  • Apache Cassandra DataStax Certification
  • Linux Foundation Linux Certification
  • Java SE Programmer Certification
  • DAS-C01

Furthermore, you will also be rewarded with IBM certificate for the respective IBM courses upon completion.

  • Spark MLlib
  • Python for Data Science
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Industry Trends

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends – the possibilities are endless and our community has something for everyone!

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hackathons-
career-services
major-announcements
-collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 20+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions and that will help you stay on track with your up skilling objective.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learners’ educational background, past experience, and future career aspirations.

Assured Interviews

After 80% of the course completion

Assured Interviews upon submission of projects and assignments. Get interviewed by our 500+ hiring partners.

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

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Course Fees

Self Paced Training

  • 277 Hrs e-learning videos
  • Flexible Schedule
  • Lifetime Free Upgrade

$527

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Frequently Asked Questions

What Is Intellipaat’s Masters Course And How It Is Different From Individual Courses?

Intellipaat’s Masters Course is a structured learning path specially designed by industry experts which ensures that you transform into Big Data expert. Individual courses at Intellipaat focus on one or two specializations. However, if you have to masters big data then this program is for you

3 technical 1:1 sessions per month will be allowed.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Learners are required to submit the mandatory assignments, project work and quizzes for receiving the Intellipaat verified certificates.

Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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