Course Curriculum

Azure Databricks Course Syllabus :

Class 1:
 ADB_Class 1_Apache Spark Introduction

Class 2:
 ADB_Class 2_Apache Spark Architecture

Class 3:
 ADB_Class 3_Apache Spark_DriverNode Internals

Class 4:
 ADB_Class 4_Apache Spark_Worker Node Internals

Class 5:
 ADB_Class 5_Azure Databricks Introduction

Class 6:
 ADB_Class 6_Create Azure Databricks Workspace

Class 7:
 ADB_Class 7_Create Azure Databricks All-Purpose Cluster

Class 8:
 ADB_Class 8_Databricks All-Purpose Cluster_Databricls Pools_Spot Instances

Class 9:
 ADB_Class 9_RDD(Reslient Distributed Dataset)_Introduction

Class 10:
 ADB_Class 10_RDD_Types of Operations_Types of Transformations

Class 11:
 ADB_Class 11_Introduction To Databricks Utilities(dbutils Module)

Class 12:
 ADB_Class 12_Databricks File System Utility_Commands

Class 13:
 ADB_Class 13_Creation of Structured API_DataFrame

Class 14:
 ADB_Class 14_Creation of DataFrame_Schemas

Class 15:
 ADB_Class 15_Data Ingestion_Azure BlobStorage

Class 16:
 ADB_Class 16_Data Ingestion_Mount Azure BlobStorage To DBFS

Class 17:
 ADB_Class 17_Data Ingestion_Direct Access to Azure BlobStorage Using Account Key

Class 18:
 ADB_Class 18_Azure Blob Storage_ABFS_Account Access Keys_Direct Access

Class 19:
 ADB_Class 19_ADLS Gen2_ABFS_OAuth2.0 with Azure Service Principal

Class 20:
 ADB_Class 20_ADLS Gen2_ABFS_Access Key_SAS Token

Class 21:
 ADB_Class 21_Azure SQL Database_Data Ingestion

Class 22:
 ADB_Class 22_Reading CSV Files_User Defined Schema

Class 23:
 ADB_Class 23_Reading_SingleLine_MultiLine_Simple JSON Files

Class 24:
 ADB_Class 24_Reading_MultiLine_Complex JSON Files

Class 25:
 ADB_Class 25_PySpark_Explode Function_Array_Map

Class 26:
 ADB_Class 26_Reading_Writing_XML File formats

Class 27:
 ADB_Class 27_Reading_Writing_Excel File formats

Class 28:
 ADB_Class 28_Reading_Writing Data _Snowflake

Class 29:
 ADB_Class 29_Reading_Writing Data _Azure Synapse Dedicated SQL Pool

Class 30:
 ADB_Class 30_Batch ETL Processing

Class 31:
 ADB_Class 31_Batch ETL Processing

Class 32:
 ADB_Class 32_Batch ETL Processing_Replace Nulls with Literals

Class 33:
 ADB_Class 33_Batch ETL Processing_GroupBy_Aggregation Processing

Class 34:
 ADB_Class 34_Batch ETL Processing_GroupBy_Aggregation Processing

Class 35:
 ADB_Class 35_Batch ETL Processing_PySpark_Join Types

Class 36:
 ADB_Class 36_Batch ETL Processing_PySpark_Union_UnionAll

Class 37:
 ADB_Class 37_Batch ETL Processing_PySpark_Distinct_DropDuplicates Methods

Class 38:
 ADB_Class 38_Spark Structured Streaming API

Class 39:
 ADB_Class 39_Data Lake Introduction

Class 40:
 ADB_Class 40_Delta Lake Introduction

Class 41:
 ADB_Class 41_Delta Lake Features_BigData File Formats

Class 42:
 ADB_Class 42_Delta Lake Creation

Class 43:
 ADB_Class 43_Create Delta Table

Class 44:
 ADB_Class 44_Create Delta Table__Spark SQL

Class 45:
 ADB_Class 45_Delta Lake Table_PySpark_DataFrame

Class 46:
 ADB_Class 46_Delta Lake_OPTIMIZE and ZORDER_Performance Optimization

Class 47:
 ADB_Class 47_Delta Lake_Delta Cache

Class 48:
 ADB_Class 48_Delta Table Instance

Class 49:
 ADB_Class 49_Create Database_SparkSQL

Course Overview

Azure Databricks Training in Bangalore, India

Azure Databricks is a cloud-based analytics service offered by Microsoft Azure in collaboration with Databricks. It provides an optimized and collaborative Apache Spark-based environment for big data analytics and machine learning. Azure Databricks combines the power of Apache Spark's distributed processing capabilities with the scalability and ease of use of Azure's cloud infrastructure.

Here are some key features and benefits of Azure Databricks:

1. Unified Analytics Platform: Azure Databricks provides a unified workspace for data engineers, data scientists, and business analysts to collaborate on data exploration, processing, and visualization. It offers a single platform for data ingestion, preparation, model training, and deployment.

2. Scalability and Performance: Leveraging the distributed computing power of Apache Spark, Azure Databricks enables processing large volumes of data at scale. It can automatically scale resources up or down based on workload requirements, ensuring high-performance analytics and reduced processing times.

3. Integration with Azure Services: Azure Databricks seamlessly integrates with other Azure services, such as Azure Data Lake Storage, Azure SQL Data Warehouse, Azure Blob Storage, and Azure Machine Learning. This allows you to leverage the full capabilities of Azure's ecosystem to build end-to-end analytics solutions.

4. Collaboration and Productivity: Azure Databricks provides a collaborative workspace where teams can work together on data analytics projects. It supports version control, notebook sharing, and real-time collaboration, making it easier for teams to iterate on data workflows and share insights.

5. Built-in Machine Learning: Azure Databricks includes libraries and tools for machine learning, such as MLflow and the MLlib library. It supports popular machine learning frameworks like TensorFlow and PyTorch, enabling data scientists to build and deploy models at scale.

6. Security and Compliance: Azure Databricks incorporates Azure's robust security and compliance features. It offers built-in authentication, role-based access control (RBAC), encryption at rest and in transit, and auditing capabilities. It also complies with industry standards and regulations, such as GDPR and HIPAA.

These are just a few highlights of Azure Databricks. It provides a powerful and flexible environment for big data processing, analytics, and machine learning, making it easier for organizations to derive insights from their data efficiently.

Azure Databricks training(ADB) in Ameerpet, Hyderabad is a fast, easy,  and collaborative Apache spark-based analytics platform. It accelerates innovation by bringing data science data engineering and business together. Making the process of data analytics more productive secure scalable and optimized for Azure.

Azure Databricks Online Training in Hyderabad

Azure Databricks is a cloud-based Apache Spark platform provided by Microsoft Azure. It enables organizations to process large amounts of data and perform advanced analytics using Spark's distributed computing capabilities. To effectively use Azure Databricks, training and learning resources are available. However, since my knowledge cutoff is in September 2021, I can provide information on the training options available at that time.

1. Azure Databricks Documentation: The official Azure Databricks documentation provides comprehensive guides, tutorials, and examples to help users get started with the platform. It covers a wide range of topics, including data ingestion, data processing, machine learning, and more.

2. Databricks Academy: Databricks Academy offers self-paced online courses and certifications for Azure Databricks. These courses cover various aspects of working with Azure Databricks, such as data engineering, data science, machine learning, and SQL analytics. The training materials include video lectures, hands-on exercises, and quizzes to assess your understanding.

3. Microsoft Learn: Microsoft Learn is a platform that provides free, interactive learning resources for various Microsoft technologies, including Azure. It offers a collection of modules and learning paths related to Azure Databricks. These modules typically consist of text-based lessons, demonstrations, and interactive coding exercises.

4. Training Partners and Courses: Microsoft has a network of training partners that offer instructor-led training courses for Azure Databricks. These courses are often conducted in a classroom or virtual setting and provide a more structured learning experience. You can check the Microsoft Learning Partners directory to find a training partner offering Azure Databricks courses.

It's important to note that the availability of training resources and offerings may have changed since my knowledge cutoff date. For the most up-to-date and detailed information, I recommend visiting the official Microsoft Azure Databricks documentation and exploring the training resources provided by Microsoft.

Q: What is Azure Databricks?

A: Azure Databricks is a cloud-based analytics platform provided by Microsoft Azure, which integrates Apache Spark with the Azure cloud ecosystem. It allows users to process and analyze large volumes of data using distributed computing capabilities of Apache Spark.

Q: What are the key features of Azure Databricks?

A: Azure Databricks offers several key features, including interactive notebooks for collaborative data exploration and analysis, Spark-based data processing capabilities, optimized data storage, automated cluster management, and integration with other Azure services.

Q: What programming languages does Azure Databricks support?

A: Azure Databricks supports multiple programming languages, including Scala, Python, SQL, R, and Java, allowing users to leverage their preferred language for data processing and analysis.

Q: How does Azure Databricks facilitate collaborative data exploration?

A: Azure Databricks provides interactive notebooks, which allow multiple users to work on the same project simultaneously, making it easy to collaborate, share code, and visualize data in real-time.

Q: What are Spark clusters in Azure Databricks?

A: Spark clusters in Azure Databricks are computing resources used for data processing. They can be easily created and scaled based on the workload requirements, ensuring efficient data processing at any scale.

Q: How does Azure Databricks enhance Apache Spark's capabilities?

A: Azure Databricks enhances Apache Spark by providing a fully managed and optimized platform in the cloud. It streamlines cluster management, automates performance tuning, and integrates seamlessly with other Azure services.

Q: Can I integrate Azure Databricks with other Azure services?

A: Yes, Azure Databricks can be integrated with various Azure services like Azure Data Lake Storage, Azure SQL Database, Azure Blob Storage, Azure Synapse Analytics, and more, allowing you to build end-to-end data analytics solutions.

Q: Is Azure Databricks suitable for big data processing?

A: Yes, Azure Databricks is designed to handle big data processing efficiently. It can scale horizontally to process large volumes of data and distribute the workload across multiple nodes for faster and parallel data processing.

Q: How can I optimize data storage in Azure Databricks?

A: Azure Databricks supports various data storage options, including Delta Lake, which provides optimized storage for big data workloads, ensuring reliability, versioning, and high-performance data access.

Q: Can I use Azure Databricks for real-time data analytics?

A: Yes, Azure Databricks can be used for real-time data analytics by integrating with Azure Stream Analytics or other real-time data streaming services. This enables processing and analyzing data as it arrives.

Q: How can I learn Azure Databricks?

A: You can learn Azure Databricks through official Microsoft training courses, online tutorials, documentation, and hands-on practice with real-world data analytics projects.

Q: What job roles are suitable for professionals with Azure Databricks skills?

A: Professionals with Azure Databricks skills can pursue roles such as Data Engineer, Data Analyst, Data Scientist, Big Data Developer, and Business Intelligence Developer in organizations focused on data analytics and big data processing.

Q: Is prior knowledge of Apache Spark required to learn Azure Databricks?

A: While prior knowledge of Apache Spark is beneficial, it is not mandatory to learn Azure Databricks. The platform provides user-friendly tools and interfaces to help users get started without extensive Spark knowledge.

Question 1: What is Azure Databricks, and why is it important for data engineering and analytics?

Answer 1: Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform provided by Microsoft Azure. It is essential for data engineering and analytics because it allows organizations to process large volumes of data, perform advanced analytics, and build machine learning models efficiently. It promotes collaboration among data engineers, data scientists, and analysts, making it a powerful tool for data-driven decision-making.

Question 2: Is Azure Databricks training suitable for beginners with no prior experience in big data or Apache Spark?

Answer 2: Yes, Azure Databricks training at BESTWAY Technologies is designed to accommodate beginners. The courses typically start with foundational concepts and gradually progress to more advanced topics, making it accessible to learners with varying levels of experience.

Question 3: What are the key topics covered in Azure Databricks training at BESTWAY Technologies?

Answer 3: Azure Databricks training typically covers a wide range of topics, including data processing with Apache Spark, data exploration and visualization, machine learning, stream processing, and best practices for building scalable and efficient data workflows.

Question 4: How long does it usually take to complete Azure Databricks training at BESTWAY Technologies?

Answer 4: The duration of Azure Databricks training can vary depending on the specific course and the depth of coverage. BESTWAY Technologies offers flexible training options, including short-term courses and more comprehensive programs, with varying durations.

Question 5: Are there any prerequisites for enrolling in Azure Databricks training?

Answer 5: While prior experience in big data technologies or Apache Spark can be beneficial, there are typically no strict prerequisites for introductory Azure Databricks courses. Familiarity with data concepts and programming fundamentals can be advantageous but is not mandatory.

Question 6: Does Azure Databricks training at BESTWAY Technologies include certification preparation?

Answer 6: Certification is usually a separate process from training, but BESTWAY Technologies may offer guidance on Azure Databricks certification exams and provide preparation materials to help students prepare for relevant certifications.

Question 7: Are there hands-on exercises and labs in Azure Databricks training?

Answer 7: Yes, hands-on practice is a significant component of Azure Databricks training at BESTWAY Technologies. Students often have access to Azure Databricks environments to work on practical exercises and real-world data engineering and analytics projects.

Question 8: What career opportunities can I pursue after completing Azure Databricks training?

Answer 8: After completing Azure Databricks training, you can pursue various career opportunities, including roles such as data engineer, data scientist, big data analyst, and machine learning engineer, in industries such as finance, healthcare, e-commerce, and more.

Question 9: Can I access training materials and resources after completing the course at BESTWAY Technologies?

Answer 9: BESTWAY Technologies often provides access to course materials and resources for a specified period after course completion, allowing you to review and reinforce your learning.

Question 10: Is job placement assistance offered after completing Azure Databricks training at BESTWAY Technologies?

Answer 10: BESTWAY Technologies may offer job placement assistance or career support services, such as resume building and interview preparation, to help students transition into Azure Databricks-related roles. It's advisable to inquire about these services when enrolling in a training program.

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Reviews

Azure Databricks Rated 4.5 based on 4 reviews.

By: Pranav Agrawal, Rating:
I am really happy with Bestway Azure Databricks training. The training was well-structured and comprehensive, and the instructor was very knowledgeable. I learned a lot about Azure Databricks and I feel confident that I can use it to solve real-world data problems. I would definitely recommend Azure Databricks training to anyone who is interested in learning this powerful tool.

By: Aarav Sharma, Rating:
Azure Databricks training covered a wide range of topics, from the basics to advanced concepts like machine learning and artificial intelligence. The instructor was very knowledgeable and experienced, and he did a great job of explaining the concepts in a clear and concise way. I also appreciated the hands-on exercises, which helped me to solidify my understanding of the material. I recommend Azure Databricks training form Bestway technologies.

By: Sudhakar, Rating:
Learning about a powerful cloud-based platform for data science and engineering through Azure Databricks training is a terrific idea. The program covers a wide range of topics, including machine learning and artificial intelligence as well as the fundamentals of Azure Databricks. Anyone who wants to understand how to utilize this crucial tool for data analysis and machine learning should take Azure Databricks training, in my opinion.

By: Juhi, Rating:
The Azure Databricks Online Training at BESTWAY Technologies is worth every moment. The trainers are knowledgeable and passionate about Azure Databricks. The course content is comprehensive, and the hands-on practice is eye-opening. I highly recommend this training.

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