Big Data has a significant impact on businesses worldwide, with applications in a wide range of industries such as healthcare, insurance, transport and logistics, and customer service. data is being generated at an exponential rate. Business data generation is increasing at a similarly rapid rate. Only a small percentage of business data is structured data in rows and columns of databases. This data proliferation requires a rethinking of traditional techniques for capture, storage, and processing. Big data is a term that describes data sets so big they can’t be managed with traditional database systems. Big Data is also a collection of tools and techniques aimed at solving these problems. This learning path covers the current thinking and state of the art for managing and manipulating large data sets using the techniques and tools of Big Data

• Training Type

Training

• Topics

Lesson 1 - What is Big Data?
Lesson 2 - Big Data: Beyond the Hype
Lesson 3 - Big Data and Data Science
Lesson 4 - Use Cases
Lesson 5 - Processing Big Data

Data Engineering with Hadoop
Lesson 1 - Introduction to Hadoop
Lesson 2 -Hadoop Architecture
Lesson 3 -Hadoop Administration
Lesson 4 -Hadoop Components

Data Engineering with Scala
Lesson 1 - Introduction
Lesson 2 - Basic Object-Oriented Programming
Lesson 3 - Case Objects and Classes
Lesson 4 - Collections
Lesson 5 - Idiomatic Scala

• Pre-requisites

The course is ideal for anyone who wishes to pursue a career in data engineering. There are no prerequisites to take this course, but prior knowledge of the listed skills and technologies are beneficial, including:

- Algorithms and data structures
- SQL
- Programming knowledge of Python and Java
- Cloud platforms and distributed systems
- Data pipelines

• Audience

- IT professionals
- Banking and finance professionals
- Database administrators
- Beginners in the data engineering domain
- Students in UG/ PG programs

• Related Courses

- Big Data Hadoop and Spark Developer
- Pyspark Training
- Big Data and Hadoop Administrator
- MongoDB Developer and Administrator
- Apache Cassandra
- Apache Spark and Scala

• Value of Training

- Understand what Big Data is, sources of Big Data, and real-life examples
- Learn about the key difference between Big Data and Data Science
- Master how to use Big Data for operational analysis and better customer service
- Know the Ecosystem of Big Data and Hadoop framework
- Understand Hadoop’s architecture and primary components, such as
- MapReduce and Hadoop Distributed File System (HDFS)
- Add and remove nodes from Hadoop clusters, check the available disk space on each node, and modify configuration
parameters
- Learn about Apache projects that are part of the Hadoop ecosystem, including Pig, Hive, HBase, ZooKeeper, Oozie, Sqoop, Flume, and more
- Create your own Scala Project
- Understand basic object-oriented programming methodologies in Scala
- Work with data in Scala such as pattern matching, applying synthetic methods, handling options, failures, and futures

• Training Hours

40 Hours