Become a Certified Big Data Architect
The Big Data Architect program is a 360° training program offered by Cognixia to professionals who are seeking to deepen their knowledge in the field of Big Data. This program is customized based on current industry standards that comprise the major sub-modules as a part of the training process. This program is designed by industry experts to provide hands-on training with tools that are used to speed up the training process.
The program is inclusive of full-fledged training courses on Java, Hadoop, MongoDB, Scala Programming, and Spark and Scala Development, all of which are found to be quite essential skills for Big Data Architects. These modules put together will provide a solid foundation and give a more competitive edge in the learning process.
This course is specifically targeted to passionate professionals who are willing to get promoted to the next level in Big Data Architecture and have already gained expertise at the basic level of Java Development.
Why take 360° Master’s Program Training in Big Data Architect?
Cognixia’s Big Data Architect Program will enable candidates to:
- Get exposure to real-life projects that will help them create high-quality Java programs by developing and implementing the Java Framework.
- Conduct full-fledged Hadoop development and implementation with excellence.
- Load information from disparate data sets and translate complex, functional and required technicalities into detailed design.
- Implement Hive & Pig, HBase, MapReduce Integration, and Advanced Indexing.
- Learn essential NoSQL concepts and get acquainted with the query language, indexes, and MongoDB’s scalability and high-quality features.
- Impart in-depth knowledge of Big Data processing using Hadoop and Spark environment with Spark and Scala module.
Overview of the Modules
A rigorous 126 hours of training would be given to candidates, wherein they would study the following five major modules and significant case studies at the end of the program.
- Java Essentials
Under this module, candidates will learn about OOPS concepts, and core and advanced Java, Servlets, and JSP technology.
- Big Data Hadoop Developer Program
This program is designed to educate candidates about Linux and Big Data Virtual Machines (VM). Candidates would be taught about the Hadoop Distributed File System (HDFS), its interface, features, and its application in fault tolerance. An overview of MapReduce (theoretical and practical), Hadoop Streaming (developing and debugging non-Java MR programs – Ruby and Python), Bulk Synchronous Parallel (BSP) – an alternative to MapReduce – and higher-level abstractions for MapReduce (Pig and Hive) are other interesting topics students would be learning under this module. In the case studies, candidates will be using Pig, HBase, Hive, and MapReduce to perform Big Data analytics learned in the course. The first case study on Twitter Analysis and the other one on Click-Stream Analysis would give a complete understanding of some interesting data analysis facts and concepts.
In this module, candidates will get an understanding of MongoDB, its installation, advantages, syntaxes, and queries. They will gain an understanding of how NoSQL suits Big Data needs. Apart from this, the course will also cover CRUD concepts, MongoDB security, and MongoDB administration activities. A hands-on Mongo DB project will show how to work with the MongoDB Java Driver and how to use MongoDB as a Java Developer.
- Scala Programming
Like Java, Scala is an object-oriented programming language, and this module has been designed to impart an in-depth knowledge of programming in Scala. The module is based on the 60:40 ratio – 60% practical sessions and 40% theoretical classes. Candidates will learn about functional programming principles, exception handling, and XML manipulating in Scala.
- Apache Spark and Scala Development Program
The objective of this program is to deliver a clear understanding of Apache Spark & Scala concepts. It will provide an overview of the Hadoop ecosystem, Hive, GraphX, and Spark Machine Learning libraries (Spark MLlib). Candidates will also learn Spark RDD, and how to write and deploy Spark applications.
Each of the modules would be followed by the practical assignments that are to be completed before the commencement of next class, to ensure candidates properly learn and clear all their doubts before moving ahead.
Who can take this training?
This course is designed for tech-savvy individuals who seek in-depth knowledge in the field of Big Data. Moreover, it offers promising benefits to fresher, experienced developers and architects, corporate IT professionals, engineers, and other professionals.
Pre-requisites for Big Data Architect Course
Our industry experts would give candidates the required information to be a Big Data Architect. With that said, there are no pre-requisites as such for learning this program. However, knowledge of basic programming concepts will be beneficial, but certainly not a mandate.
- Features of Java
- Java Basics
- Classes and Objects
- Garbage Collection
- Java Arrays
- Referring Java Documentation
- Wrapper classes
- Abstract Classes
- 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
- Byte Streams
- Character Streams
- Object Serialization & Object Externalization
- Introduction to GUI Programming (Swing)
- Introduction to Multithreading
- Thread Lifecycle
- Thread Priorities
- Using wait() & notify()
- JDBC Architecture
- Using JDBCI API
- Transaction Management
Java Servlet Technology
- What is a Servlet?
- Servlet Life Cycle
- Initializing a Servlet
- Writing Service Methods
- Getting Information from Requests
- Constructing Responses
- ServletContext and ServletConﬁg Parameters
- Attributes – Context, Request and Session
- Maintaining Client State – Cookies/URL rewriting/Hidden Form Fields
- Session Management
- 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 Content
- Creating Dynamic Content
- Using Implicit Objects within JSP Pages
- JSP Scripting Elements
- Including Content in a JSP Page
- Transferring Control to Another Web Component – communication with servlet
- Param Element
- JavaBeans Component Design Conventions
- Why Use a JavaBeans Component?
- Creating and Using a JavaBeans Component
- Setting JavaBeans Component Properties
- Retrieving JavaBeans Component Properties
- Custom Tags
Introduction to Scala
- A brief history of the Java platform to date
- Distinguishing between the Java language and platform
- Pain points when using Java for software development
- Possible criteria for an improved version of Java
- How and why the Scala language was created?
Key Features of the Scala Language
- Everything is an object
- Class declarations
- Data typing
- Operators and methods
- Pattern matching
- Anonymous and nested functions
Basic Programming in Scala
- Build in types, literals, and operators
- Testing for equality of state and reference
- Conditionals, simple matching and external iteration
- Working with lists, arrays, sets and maps
- Throwing and catching exceptions
- Adding annotations to your code
- Using standard Java libraries
- Using Scala with in java application and vice-versa
OO Development in Scala
- A minimal class declaration
- Understanding primary constructors
- Specifying alternative constructors
- Declaring and overriding methods
- Creating base classes and class hierarchies
- Creating traits and mixing them into classes
- How a Scala inheritance tree is linearized?
Functional Programming in Scala
- Advanced uses of for expressions
- Understanding function values and closures
- Using closures to create internal iterators
- Creating and using higher order functions
- Practical examples of higher order functions
- Currying and partially applied functions
- Creating your own Domain Speciﬁc Languages(DSL’s)
Exception handling in Scala
Try catch with case
Pattern Matching in Depth
- Using the match keyword to return a value
- Using case classes for pattern matching
- Adding pattern guards to match conditions
- Partially specifying matches with wildcards
- Deep matching using case constructors
- Matching against collections of items
- Using extractors instead of case classes
Test Driven Development in Scala
Writing standard JUnit tests in Scala
Conventional TDD using the ScalaTest tool
Behavior Driven Development using ScalaTest
Using functional concepts in TDD
- XML Manipulating in Scala
- Using Scala to read and write XML using diﬀerent parsers (Dom, Sax)
- Working with XML literals in code
- Embedding XPath like expressions
- Using Pattern Matching to process XML data
- Serializing and de-serializing to and from XML
- Scala with database transaction
- Writing Concurrent Apps
- Issues with conventional approaches to multi-threading
- How an actor-based approach helps you write thread-safe code?
- The Scala architecture for creating actor-based systems
- Diﬀerent coding styles supported by the actor model
- XML Manipulating in Scala
- Scala with JAXB
- Scala to call/consume a REST/SOAP service
- Scala with logging information
- Using Scala in web application (JSP, Servlet)
- Module Outline
- What We Will Build
- History of Play!
- Downloading Play!
- The Play Command
- Compiling and Hot Deploy
- Project Structure
- Error Handling
- The Router
- Router Mechanics
- Routing Rules
- Play! Routes
- Play! Routes: HTTP Verbs
- Play! Routes: The Path
- Play! Routes: The Action Call
- Routing in Action
Controllers, Actions, and Results
- Session and Flash Scope
- Request Object
- Implementing the Contacts Stub Controller
- Play! Views
- Static Views
- Passing Arguments
- Partials and Layouts
- Accessing the Session Object
- The Asset Route
- Agnostic Data Access
- The Domain Model
- Finder and Listing Contacts
- The Form Object and Adding a Contact
- Editing a Contact
- Deleting a Contact
The Global Object
- The Global Object
- Global Object Methods
We provide 126 hours of live online training, including live POC and assignments.
Live and interactive online sessions with an industry expert instructor.
Expert technical team available for query resolution.
We provide lifetime Learning Management System (LMS) access, which you can access from across the globe.
We strive to offer the best price to our customers with the guarantee of quality service levels.
After completing the course, you will appear for an assessment from Cognixia. Once you pass, you will be awarded a course completion certificate.
Our industry expert veterans are Cloudera and Hortonworks professionals with more than 12 years of experience in the field.
To attend the live virtual training, at least 2 Mbps of internet speed would be required.
We provide 126 hours of live online training, including live POC and assignments.
Candidates need not worry about losing any training session. They will be able to view the recorded sessions available on the LMS. We also have a technical support team to assist the candidates in case they have any query.
Access to the Learning Management System (LMS) will be for lifetime, which includes class recordings, presentations, sample code, and projects.
The trainer was very knowledgeable, I feel so great to join the training program with Cognixia. The trainer has vast experience in big data, very professional in delivering the sessions. Even the cluster configuration session went really well. I would recommend Cognixia to my friends and colleagues in taking up certification trainings.
The course curriculum is dynamic and changes according to the industry standards. They train you to be job-ready. The certification has changed my work profile to Big Data Expert Analyst.
The trainer has got excellent training skills and immense knowledge on Big Data field with crisp course content. I am grateful to have pursued this training; it has definitely benefited me.
The course is designed according to the industry standards. It has helped me a lot in my current profile. There was excellent dedication shown by the technical team. The required material was uploaded immediately after the training session.
The training modules that cognixia posses are excellent! The trainer’s name was enough for me to enroll for Big Data Architect program training. He has excellent knowledge and trained me well in this field. Overall it was a superb experience.
The training was fruitful as it covered new topics meeting the industry standards. The sessions were interactive with practical industrial examples which made me understand the nitty-gritty of the course applications.
Trainers were at par with the course so they possessed deep knowledge and understanding of the field and made the session very interesting. The sessions were excellent and interactive that has enhanced my skills to meet the industry standards.
I am well-satisfied with the training program and the structure. I was taught from the basic level to the most advanced level in Big Data Architect program. It has transformed my job position to a senior big data architect.
I thank the entire team including the trainers, technical team and the people who encouraged me to enroll for this course. This course is feasible for beginners as well as for people who expertise in Big Data Hadoop Development.
Overall it was a fruitful experience. Completing all the 5 modules has drastically transformed my skills for the better. This program is very well structured and helps those who want to master the skills of Big Data.
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- Students 26654
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