DATA ENGINEER

DATA ENGINEER

4.5 out of 5 based on 3200 reviews

Join the program and get the opportunity to learn under the guidance of an data engineer specialist.

DATA ENGINEER

Expertise

prof trained

80000+

Professionals Trained
batch image

50+

Industry Expert Trainers
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8 Branches

In NCR
corporate

2500+

Corporate Served

Course Duration

--

Certificate

Yes

Live Project

--

Training Mode

Classroom / Online

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Data Engineer Course

Ducat's Data Engineering Certification Training Course using Azure is designed by IT experts. In this training, you will be taught concepts like data warehousing, Hadoop, Databricks, Delta lake, Delta Live table, and many more with industry-relevant projects. This Data Engineer ( Hadoop) Course provides real-world experience in various sectors.

People often confuse Data Engineers and Big data Hadoop developers. Data Engineering technology is migrated with Microsoft Azure (cloud) and has some more additional technologies than Big data Hadoop developers, this is the basic difference between data engineers and Big data Hadoop developers.

Course Overview of Data Engineering

In this Ducat's Data Engineer (Hadoop) course, you will get a deep understanding of cloud services of Azure and AWS, data transformation, SQL, Spark, python and many more. You will be given real-world projects under the guidance of subject matter experts so that you can get the practical learning which will help you to become an expert in core concepts like pulling data from multiple sources, creating cloud data warehouses, creating production-ready ETL, Data modelling and many more.

WHY CHOOSE DUCAT FOR DATA ENGINEER COURSE?

Looking to unlock the exciting world of Big Data? Ducat's Data Engineer (Hadoop) course in Noida can be your launchpad! Here's why Ducat stands out for students like you:

  • Master in-demand skills: Gain expertise in Hadoop, a core framework for handling massive datasets. Learn data warehousing, data transformation, and tools...

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Learn The Essential Skills

Learn The Essential Skills

Earn Certificates And Degrees

Earn Certificates And Degrees

Get Ready for The Next Career

Get Ready for The Next Career

Master at Different Areas

Master at Different Areas

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What you will learn?

  • Hadoop Fundamentals: Understand the core concepts of Hadoop ecosystem, including HDFS (Hadoop Distributed File System) and MapReduce, essential for managing and processing large-scale data efficiently.
  • Data Ingestion and Storage: Learn techniques for ingesting various types of data into Hadoop clusters, and explore best practices for organizing and storing data effectively to optimize processing performance.
  • Data Processing with MapReduce: Gain proficiency in developing MapReduce programs to process and analyze massive datasets, enabling you to extract valuable insights and perform complex computations.
  • Hadoop Ecosystem Components: Explore additional components of the Hadoop ecosystem such as Hive, Pig, HBase, and Spark, and understand how to leverage these tools for different data processing and analysis tasks.Scalability and Performance Optimization: Master techniques for optimizing Hadoop cluster performance and scalability, including resource management, tuning configurations, and implementing parallel processing strategies to handle increasing data volumes efficiently.

Skill you will gain

  • Hadoop Administration

  • Data Warehousing

  • Big Data Analytics

  • Data Integration

Explore Modules of this course

Data warehousing Concepts

Need for Data Warehouse DWH Characteristics Data Warehouse Architecture Data marts in DWH Data Mining Difference between Data Warehouse and Data Mart OLTP vs OLAP Dimension & Types of dimensions Junk dimensions

Hadoop

Hadoop Overview Hadoop Architecture Hadoop Installation Hadoop Components HDFS HDFS command

Databricks

Introduction to Databricks Databricks Architecture Databricks Concepts Creating and configuring clusters in Databricks Free Account and Free Subscription For Databricks How to create Databricks Cluster, Notebook & quick tour on notebook options

Beginner & Intermediate

Just Enough Python for Spark Spark Overview Spark Architecture & Internal Working Mechanism Spark components PySpark installation PySpark Data structure (RDD, Dataframe, Dataset) Pyspark utility command (DBUtils) Pyspark Read TSV Files and PIPE Seperated CSV Files Pyspark Read Parquet file Pyspark Read text file Pyspark Read Avro file Pyspark Read CSV file with multiple delimiters at different positions PySpark Write TSV file Pyspark: Handling Null - Part1 Pyspark Functions| Part 2 : Array_Intersect Pyspark Functions| Part 3 : Array_Except Pyspark Functions| Part 4 : Array_Sort

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