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Big Data Architect Training

Big Data Architect Training

About Big Data Architect Training

Our Big Data architect course lets you gain proficiency in Big Data and provides you in-depth knowledge on big data platforms like Hadoop, Spark, NoSQL databases along with detailed exposure of analytics and ETL by working on tools like Informatica. This program is specially designed by Industry experts and you'll get courses with industry based project.

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05 Dec 2023 $1100   $1000
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About Course

What is Big Data Architect?

Big Data Solutions Architecture is an architecture domain that aims to address specific big data problems and requirements. Big data solutions architects are trained to describe the structure and behavior of a big data solution and how that big data solution can be delivered using big data technologies like Java, Hadoop, MongoDB, Scala Programming, and Spark and Scala Development.

What does a Big Data Architect do? 

Big data architect has responsibilities to solve big data problems by structuring and analyze the behavior of data using data technology. Big data architect handles a large-scale database, analyzing the patterns of data to make strong and accurate business decisions. They must be a strong team leader, ability to mentor and collaborate with the other teams.

Why learn Big Data Architect?

Big data is the fastest growing and most promising technology jobs like big data Engineer, big data solution architect are in huge demand. This big data architect course can assist you to grab the best jobs domain.

Our training program has been specifically created to let you masters the Hadoop architect, along with help you gain proficiency in the business intelligence domain.

Upon completion of the training, you'll be well-versed in extracting valuable insights from data and convert it into business insights. This way you'll be able to apply for the top jobs within the big data ecosystem.

What you’ll learn in Big Data Hadoop Administration Training?

  • Introduction to the Hadoop ecosystem
  • Working with HDFS & MapReduce
  • Real-time analytics with Apache Spark
  • ETL in the business intelligence domain
  • Working on large amounts of data with NoSQL databases
  • Real-time message brokering system.
  • Hadoop analysis and testing.
  • Big Data Hadoop & Spark
  • Apache Spark & Scala
  • Splunk Developer & Admin
  • Informatica
  • Tableau Desktop 10
  • Python for Data Science
  • Java Essentials
  • MongoDB

Who should take this course?

  • Data Science & Big Data professionals, Software developers
  • Business Intelligence professionals, Information Architects, Project Managers
  • Graduates who want to be a Big Data Architect


  • There are no prerequisites for taking this training program.
  • Having a basic knowledge of Java Programming will be a plus.

Big Data Architect Course Highlights

  • Big Data Hadoop & Spark
  • Apache Spark & Scala
  • Splunk Developer & Admin
  • Informatica
  • Tableau Desktop 10
  • Python for Data Science
  • Java Essentials
  • MongoDB
  • Working on real-life industry-based projects
  • Mock interview sessions, resume services and Interview questions to prepare you to attend interviews with confidence.
  • Access to the instructor through email to address any questions.

How EnhanceLearn Training can help you

  • 48 Hours of hands-on session per batch and once enrolled you can take any number of batches for 90 days
  • 24x7 Expert Support and GTA (Global Teaching Assistant, SME) support available even to schedule a one on one session for doubt clearing
  • Project Based learning approach with evaluation after each module
  • Project Submission mandatory for Certification and thoroughly evaluated
  • 3 Months Experience Certificate on successful project completion

For becoming a Big Data Architect expert, choose our best Training and Placement Program. If you are interested in joining the EnhanceLearn team, please email at

Course Curriculum

Module 1: Core Java

  • Features of Java
  • Java Basics
  • Classes and Objects
  • Java Arrays
  • Wrapper classes
  • Inheritance
  • Polymorphism
  • Abstract Classes
  • Interfaces
  • Packages
  • Introduction to Exception Handling
    • Checked/Unchecked Exceptions
    • Using try, catch, finally, throw, throws
    • Exception Propagation
    • Pre-defined Exceptions
    • User Defined Exceptions
  • Overview of Java IO Package
  • Object Serialization & Object Externalization
  • Introduction to GUI Programming (Swing)
  • Introduction to Multithreading
  • Thread Lifecycle
  • Using wait() & notify()
  • DeadLocks
  • JDBC Architecture
  • Using JDBCI API
  • Transaction Management

Module 2: Servlets and JSP

  • Java Servlet Technology
    • What is a Servlet?
    • Servlet Life Cycle
    • Initializing a Servlet
    • Writing Service Methods
    • Constructing Responses
    • ServletContext and ServletConfig Parameters
    • Attributes – Context, Request and Session
    • Maintaining Client State – Cookies/URL rewriting/Hidden Form Fields
    • Servlet Communication – include, forward, redirect
    • WEB-INF and the Deployment Descriptor
  • Java Server Pages Technology
    • What Is a JSP Page?
    • The Lifecycle of a JSP Page
    • Execution of a JSP Page
    • Different Types of Tags (directive, standard actions, bean tags, expressions, declarative)
    • Creating Static/Dynamic Content
    • Using Implicit Objects within JSP Pages
    • JSP Scripting Elements
    • JavaBeans Component Design Conventions
    • Why Use a JavaBeans Component?
    • Setting JavaBeans Component Properties
    • Retrieving JavaBeans Properties
  • New Big Data Mechanisms, including
    • Security Engine
    • Cluster Manager
    • Data Governance Manager
    • Visualization Engine
    • Productivity Portal
  • Data Processing Architectural Models, including
    • Shared-Everything and Shared-Nothing Architectures
  • Enterprise Data Warehouse and Big Data Integration Approaches
    • Series
    • Parallel
    • Big Data Appliance
    • Data Virtualization
  • Architectural Big Data Environments
    • ETL
    • Analytics Engine
    • Application Enrichment
  • Cloud Computing & Big Data Architectural Considerations, including
    • How Cloud Delivery and Deployment Models can be used to host and process Big Data Solutions
  • Big Data Solution Architectural Layers including
    • Data Sources
    • Data Ingress and Storage
    • Event Stream Processing and Complex Event Processing
    • Egress
    • Visualization and Utilization
    • Big Data Architecture and Security
    • Maintenance and Governance
  • Big Data Solution Design Patterns, including
    • Patterns pertaining to Data Ingress
    • Data Wrangling
    • Data Storage
    • Data Processing
    • Data Analysis,
    • Data Egress,
    • Data Visualization
  • Big Data Architectural Compound Patterns
  • Installation of Hadoop and Hadoop Ecosystems
  • Introduction to Big Data Hadoop.
  • Understanding HDFS & MapReduce
  • Advance Hive & Impala
  • Introduction to Pig
  • Flume, Sqoop & HBase
  • Writing Spark Applications using Scala
  • Hadoop Administration - Multi Node
  • Cluster Setup using Amazon ec2
  • Hadoop Administration – Cluster Configuration
  • Hadoop Administration - Maintenance, Monitoring and Troubleshooting
  • Oozie
  • Introduction to Spark
  • Spark Basics
  • Working with RDDs in Spark
  • Aggregating Data with Pair RDDs
  • Writing and Deploying Spark Application
  • Spark framework
  • Data frames and Spark SQL
  • Machine Learning using Spark (Mlib)
  • Spark Streaming
  • Parallel Processing
  • Spark RDD Persistence
  • Spark Streaming & Mlib
  • Improving Spark Performance
  • Spark SQL and Data Frames
  • Introduction of Scala
  • Programming in Scala
  • OO Development in Scala
  • Pattern Matching
  • Executing the Scala Code
  • Classes concept in Scala
  • Concepts of traits with example
  • Exception handling in Scala
  • Scala java interoperability
  • Scala collections
  • Test Driven Development in Scala
  • Writing standard JUnit tests in Scala
  • Conventional TDD using the ScalaTest tool
  • Behavior Driven Development using ScalaTest
  • Use case bobsrockets package
  • Splunk Development concepts
  • Basic Searching & Using Fields in Searches
  • Creating Alerts & Scheduled Reports
  • Creating and Using Macros
  • Workflow & Splunk Search Commands
  • Transforming & Reporting Commands
  • Mapping and Single Value Commands
  • Splunk Reports & visualizations
  • Analyzing, Calculating and Formatting Results
  • Correlating Events & Enriching Data with Lookups Using Pivot
  • Common Information Model (CIM) Add-On
  • Splunk configuration files
  • Splunk Deployment Management
  • Splunk Search Engine
  • Splunk User & Index Management
  • Search Scaling and Monitoring
  • Splunk Cluster implementation
  • Informatica Installation and Configuration
  • Active, passive, expression transformation
  • Sorter, Sequence Generator, Filter, Joiner transformation
  • Ranking, Union, Router Transformation
  • Syntax for Rank and Dense Rank
  • Source Qualifier Transformation and Mappings
  • Slowly Changing Dimension & advanced SCD
  • Mapplet and loading to multiple designer
  • Performance Tuning in Informatica
  • Repository Manager & Workflow
  • High Availability & Failover, working with utilities
  • Incremental Data Loading and Aggregation
  • Constraint based loading
  • XML Transformation & active look up
  • Profiling in PowerCenter
  • Database Connection & Relational Database Tables
  • Push down optimization, Partitioning, Cache management
  • Introduction to Data Visualization and Power of Tableau
  • Architecture of Tableau
  • Metadata & Data Blending
  • Creation of sets
  • Working with Filters
  • Organizing Data and Visual Analytics
  • Working with Mapping
  • Working with Calculations & Expressions
  • Working with Parameters
  • Charts and Graphs
  • Integration of Tableau with R and Hadoop
  • Basic constructs of Python language
  • Writing Object Oriented Program in Python and connecting with Database
  • File Handling, Exception Handling in Python
  • Mathematical Computing with Python (NumPy)
  • Scientific Computing with Python (SciPy)
  • Data Visualization (Matplotlib)
  • Data Analysis and Machine Learning
  • (Pandas) / Data Manipulation with Python
  • Machine Learning, Natural Language Processing (Scikit-Learn)
  • Web Scraping for Data Science
  • Python on Hadoop
  • Writing Spark code using Python
  • Working on Live Projects (as applicable)


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Big Data Architect Training
Big Data Architect Certificate
Job Overview
Key Features
Training FAQs
What does a Big Data Architect do? 

Big data architect has responsibilities to solve big data problems by structuring and analyze the behaviour of data using a data technology. Big data architect handles large-scale database, analysing the patterns of data to make strong and accurate business decisions. They must be a strong team leader, ability to mentor and collaborate with the other teams.

Why learn Big Data Architect?
I have knowledge of Linux. Do I get any further benefit while learning Hadoop?
Is SQL knowledge important in Hadoop?
What are the Technical Skills to become a Big Data Architect?
What are the preferred skills of a Big Data Architect by employers?
What platforms and java versions does Hadoop run on?
Can I install Hadoop environment on my MAC machine?
Is big data certification and training worth pursuing?
What are the benefits of Hadoop learning?
How is the job market for Hadoop professional currently in US?
What is the salary of a Big Data Architect in the US?
Do you provide demo sessions?
What if I miss a training class or session?
Who are our instructors?
How do you provide training?
Is the training interactive, how will it help me to learn?
Will I get to work on a project for this Training?
Do you provide any certification?
How will I get my certificate?
What are the services you provide for job support after training?
Do you provide job placement after the training?
What about the payment process to enroll with the Training?
I am an international student in USA looking for placement?
In how much time will I get a job, if I choose your placement service?
What if I have more queries?

More Questions? Request a call!

Ruchi Arora 
Excellent Course!

My overall experience during the Big Data Hadoop architect training was great. The course content is present in a crisp and concise manner. The videos and other study materials provided by EnhanceLearn is top-quality. I really liked the training and overall it was very satisfying. Keep up the good work EnhanceLearn.

Chitranjan Borah 
The Trainers are Marvellous

I am fan of the trainers. Both the trainers were marvellous. They explained every single topic with such ease and in-depth. There sessions were comprehensive and extremely structured. All the materials provided were also up to the latest standards. I gained high-confidence level because of this training. Thanks EnhanceLearn!

Vijay Prasad 
EnhanceLearn's Big Data Hadoop Architect training helped me

I actually want to thank myself for enrolling in the Big Data Hadoop Architect program at The training was very effective because the trainers have up to date knowledge of the topics and the concepts were very well taught. I am also looking forward to take up another advanced level training to get deep into the subject.

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