About Azure Databricks
Faculty Profile
Course Syllabus

What is Azure Databricks?

Azure Databricks is a cloud analytics platform optimized for Microsoft Azure cloud services platform where, both data science and engineering teams can work together to build end-to-end machine learning solutions. Microsoft Azure Databricks gives Azure users a single platform for Big Data processing and Machine Learning.

Key features and components:

  • Optimized Apache Spark environment
  • Productivity boost with a shared workspace and common languages
  • Turbo charge machine learning on big data
  • High-performance modern data warehousing
  • Optimized spark engine
  • Machine learning run time
  • MLflow
  • Choice of language
  • Collaborative notebooks
  • Delta lake
  • Native integrations with Azure services
  • Interactive workspaces
  • Enterprise-grade security
  • Production-ready

About the course:

Azure Databricks is an a combination of Spark, Microsoft and Databricks, that presents a just-in-time analytics platform, which empowers data personnel to easily build and deploy advanced data analytic solutions. The use of Azure Databricks by small, medium and large enterprises is gaining traction and relevance in the world of big data for many reasons.

Azure Databricks course at Version IT covers the advanced concepts of Azure Data Bricks including caching and REST API development. Our experts at the academy deliver training in Azure Data bricks. With two decades of successful training experience in the industry, Version IT is a leading Microsoft Azure training academy in Hyderabad. The syllabus combines Microsoft Windows Azure Course with practical knowledge to make sure that the learners are all set to make a career as Azure professionals as soon as they finish their course.

What you will learn in the course?

The prerequisites for learning Azure Databricks are Python programming and fundamental SQL and databases

The course comprises of the following broad concepts

  • Big data ecosystem, also with Azure Databricks.
  • Internal details of Spark
  • RDD
  • Data frames
  • Workspace
  • Jobs
  • Kafka
  • Streaming and other data sources for Azure Data bricks
  • caching and REST API development

Training Overview:

Version IT is a prominent Azure Databricks training institute in Hyderabad. Its 60hour training course includes doubt clearing sessions and one-to-one feedback by the faculty.Flexible batch timings are made available for working professionals and students.

Students will be given genuine notes, books and subject matter, so that they can easily revise and recap the training sessions at their own time and convenience. Students are given personal attention to enhance their soft skills along with technical skills during training.

Version IT offers top Azure Data bricks training in India and if you are a data engineering enthusiast, this course might just be the right one for you.

Join our Azure Databricks training in Hyderabad today to get the much needed breakthrough in your career and carve an identity for yourself in the IT industry.

Sri Ram Sr.Consultant

SRI RAM is a versatile mentor having Through knowledge in Azure Data Engineer. With his vast Experience he served in top most MNC's .With his unique teaching methods Sriram trained hundreds of students and professionals in Azure.He Guided many aspirants by assisting them to get the job Opportunities.

Module 1: Cloud Computing Concepts

  • What is the "Cloud"?
  • Why cloud services
  • Types of cloud models
    • Deployment Models
    • Private Cloud deployment model
    • Public Cloud deployment model
    • Hybrid cloud deployment model
    • Microsoft Azure,
    • Amazon Web Services,
    • Google Cloud Platform
  • Characteristics of cloud computing
    • On-demand self-service
    • Broad network access
    • Multi-tenancy and resource pooling
    • Rapid elasticity and scalability
    • Measured service
  • Cloud Data Warehouse Architecture
  • Shared Memory architecture
  • Shared Disk architecture
  • Shared Nothing architecture

Module 2: Core Azure services

  • Core Azure Architectural components
  • Core Azure Services and Products
  • Azure solutions
  • Azure management tools

Module 3: Security, Privacy, Compliance

  • Securing network connectivity
  • Core Azure identity services
  • Security tools and features
  • Azure Governance methodologies
  • Monitoring and reportingS
  • Privacy, compliance, and data protection standards

Module 4:Azure Pricing and Support

  • Azure subscriptions
  • Planning and managing costs
  • Azure support options
  • Azure Service Level Agreements (SLAs)
  • Service Lifecycle in Azure

Module 5: Introduction to Azure Databricks

  • Introduction to Databricks
  • Azure Databricks Architecture
  • Azure Databricks Main Concepts

Module 6:Azure Databricks Account Creation

  • Azure Free Account
  • Free Subscription for Azure Databricks
  • Create Databricks Community Edition Account

Module 7:Databricks Cluster Types and Notebook Options

  • Creating and configuring clusters
  • Create Notebook
  • Quick tour on notebook options

Module 8:Databricks Utilities and Notebook Parameters

  • Dbutils commands on files, directories
  • Notebooks and libraries
  • Databricks Variables
  • Widget Types
  • Databricks notebook parameters

Module 9:Databricks CLI

  • Azure Databricks CLI Installation
  • Databricks CLI - DBFS, Libraries and Jobs

Module 10:Databricks Integration with Azure Blob Storage

  • Read data from Blob Storage and Creating Blob mount point

Module 11:Databricks Integration with Azure Data Lake Storage Gen2

  • Reading files from Azure Data Lake Storage Gen2

Module 12:Databricks Integration with Azure Data Lake Storage Gen1

  • Reading Files from data lake storage Gen1

Module 12:Databricks Integration with Azure Data Lake Storage Gen1

  • Reading Files from data lake storage Gen1

Module 13:Reading and Writing CSV files in Databricks

  • Read CSV Files
  • Read TSV Files and PIPE Seperated CSV Files
  • Read CSV Files with multiple delimiter in spark 2 and spark 3
  • Reading different position Multidelimiter CSV files

Module 14:Reading and Writing Parquet files in Databricks

  • Read Parquet files from Data Lake Storage Gen2
  • Reading and Creating Partition files in Spark

Module 15:Parsing Complex Json FilesL

  • Reading and Writing JSON Files
  • Reading, Transforming and Writing Complex JSON files

Module 16:Reading and Writing ORC and Avro Files

  • Reading and Writing ORC and Avro Files

Module 17:Databricks Integration with Azure Synapse

  • Reading and Writing Azure Synapse data from Azure Databricks

Module 18:Databricks Integration with Amazon Redshift(Redshift)

  • Read and Write data from Redshift using databricks

Module 19:Databricks Integration with Snowflake

  • Reading and Writing data from Snowflake

Module 20:Databricks Integration with CosmosDB SQL API

  • Reading and Writing data from Azure CosmosDB Account

Module 21:Python Introduction

  • Python Introduction
  • Installation and setup
  • Python Data Types for Azure Databricks

Module 22:Python Data Types

  • Deep dive into String Data Types in Python for Azure Databricks
  • Deep dive into python collection list and tuple
  • Deep dive on set and dict data types in python

Module 23:Python Functions and Arguments

  • Python Functions and Arguments
  • Lambda Functions

Module 24:Python Modules and Packages

  • Python Modules and Packages

Module 25:Python Flow Control

  • Python Flow Control
  • For-Each
  • While

Module 25:Python Flow Control

  • Python Flow Control
  • For-Each
  • While

Module 26:Python File Handling

  • Python File Handling

Module 27:Python Logging Module

  • Python Logging Module

Module 28:Python Exception Handling

  • Python Exception Handlings

Module 29:Pyspark Introduction

  • Pyspark Introduction
  • Pyspark Components and Features

Module 30:Spark Architecture and Internals

  • Apache Spark Internal architecture
  • jobs stages and tasks
  • Spark Cluster Architecture Explained

Module 31:Spark RDD

  • Different Ways to create RDD in Databricks
  • Spark Lazy Evaluation Internals & Word Count Program
  • RDD Transformations in Databricks & coalesce vs repartition
  • RDD Transformation and Use Cases

Module 32:Spark SQL

  • Spark SQL Introduction
  • Different ways to create DataFrames

Module 33:Spark SQL Intenals

  • Catalyst Optimizer and Spark SQL Execution Plan
  • Deep dive on Sparksession vs sparkcontext
  • spark SQL Basics part-1
  • RDD Transformation and Use Cases

Module 34:Spark SQL Basics

  • Spark SQL Basics Part-2
  • Joins in Spark SQL

Module 35:Spark SQL Functions and UDFs

  • Spark SQL Functions part-1
  • Spark SQL Functions part-2
  • Spark SQL Functions Part-3
  • Spark SQL UDFs
  • Spark SQL Temp tables and Joins

Module 36:Databricks Delta and Implementing Dimensions SCD1 and SCD2

  • Implementing SCD Type1 and Apache Spark Databricks Delta
  • Delta Lake in Azure Databricks
  • Implementing SCD Type with and without Databricks Delta

Module 37:Databricks Integration with Azure Data Factory

  • Azure Data Factory Integration with Azure Databricks

Module 38:Databricks Streaming

  • Delta Streaming in Azure Databricks
  • Data Ingestion with Auto Loader in Azure Databricks

Module 39:Azure Databricks Projects

  • Azure Databricks Project-1
  • Azure Databricks Project-2

Module 40:Databricks Integration with Azure Devops

  • Azure Databricks CICD Pipelines

Fill the form and get 10% discount