DP-3011: Implement a Data Analytics Solution with Azure Databricks

The Implementation of a Data Analytics Solution with Azure Databricks course is a full-day training program that gives data professionals the skills they need to use Azure Databricks to build and run scalable data analytics solutions. People who take the course will learn about the Azure Databricks environment and how to use it to explore and visualize data in collaborative notebooks, create Spark clusters, and offer workspaces.  

The course explores Delta Lake’s data management capabilities, highlighting time travel, schema enforcement, and ACID transactions. Additionally, participants will get practical experience utilizing Azure Databricks Workflows to deploy workloads and Delta Live Tables to develop real-time data pipelines. Integration with Azure Data Factory is discussed, showing how to efficiently pass parameters and run notebooks inside pipelines. 

After completing this course of training, you will be able to:

  • Create workspaces in Azure Databricks and determine the platform's primary workloads and personas.
  • Use Spark to process and analyze data stored in files, build and configure Spark clusters, and comprehend the architecture of Apache Spark.
  • To efficiently manage data in Azure Databricks, use Delta Lake capabilities like time travel, schema enforcement, and ACID transactions.
  • In Azure Databricks, create and manage SQL Warehouses by configuring databases, tables, queries, and data analysis dashboards.
  • To streamline data workflows, run Azure Databricks notebooks inside Azure Data Factory pipelines, build linked services

Upcoming Batches

Loading Dates...

Key Features of DP-3011 Training:

  • Comprehensive Coverage: This course explores the fundamental elements of Azure Databricks, such as setting up SQL Warehouses, managing data with Delta Lake, using Apache Spark for large-scale data processing, allocating workspaces, and connecting with Azure Data Factory. Participants will acquire a comprehensive understanding of developing and overseeing cloud-based data analytics systems. 

  • Hands-on Practical Exercises: The course integrates interactive labs and real-world settings with an emphasis on experiential learning. Students work on tasks like setting up Spark clusters, utilizing notebooks to analyze data, putting Delta Lake capabilities like time travel and ACID transactions into practice, and using Delta Live Tables to create data pipelines. These activities develop the practical abilities necessary for real-world applications while reinforcing academic understanding.  

  • Focus on role-based learning: The course was created with data scientists, data engineers, and data analysts in mind, and it fits in with their unique duties and difficulties. In order to make sure that the learning process is pertinent and instantly applicable to participants’ job activities, the curriculum covers tasks including data ingestion, transformation, analysis, and visualization. 

  • Career Advancement: Gaining technical competency in state-of-the-art data analytics tools and processes via mastery of the skills covered in the DP-3011 course qualifies professionals for career advancement. Opportunities for advanced positions in data engineering, analytics, and cloud solution architecture are made possible by this skill, which also raises the possibility of greater pay and increases job market competitiveness. 

Who should attend DP-3011 training?

  • Data Engineers: those in charge of creating, putting into practice, and overseeing analytics and data pipelines.
  • Data Scientists: professionals want to use Azure Databricks for jobs involving machine learning and complex data processing.
  • Data Analysts: those who want to explore, transform, and visualize data with Azure Databricks.
  • Business Intelligence Developers: developers who specialize in leveraging SQL Warehouses in Azure Databricks to create dashboards and reports.
  • Cloud Solution Architects: architects working on creating effective and scalable Azure data analytics solutions.

Pre-requisites of DP 3011 course :

    To enrol in this course, it is recommended to have:
  • Foundational Azure Knowledge
  • Data Engineering Fundamentals .
  • Programming Experience-Python, SQL.

    • Learning objective of the DP-3011 Certification Training

    • Explore and Configure Azure Databricks: Understand the architecture and use cases of Azure Databricks.
    • Perform Data Analysis in Azure Databricks: Ingest data from various sources into Azure Databricks. Explore and transform data using DataFrames and Spark SQL.
    • Leverage Apache Spark for Big Data Processing: Understand the core concepts of Apache Spark and its role in big data analytics.
    • Manage Data with Delta Lake and Build and Manage Pipelines with Delta Live Tables: Build declarative, automated data pipelines with Delta Live Tables (DLT).
    • Operationalize Workloads with Databricks Workflows: Use Azure Databricks Workflows to schedule and orchestrate jobs and pipelines.

    Why choose CloudThat as your training partner for DP-3011?

    • Expert Instructors: CloudThat’s instructors are highly experienced and certified professionals with in-depth knowledge of Databricks and data engineering principles. They provide top-notch training and guidance throughout the preparation process.
    • Comprehensive Course Content: CloudThat offers a well-structured and comprehensive course curriculum that covers all the essential topics needed to excel in the Databricks Certified Data Engineer Associate exam.
    • Hands-on Labs: CloudThat emphasizes hands-on learning through practical exercises and real-world scenarios, allowing candidates to gain practical experience working with Databricks Unified Analytics Platform.
    • Flexibility: CloudThat offers flexible training options, including online and in-person classes, allowing candidates to choose the mode of learning that suits their schedule and preferences.
    • Track Record: CloudThat has a proven track record of success in training and preparing candidates for various cloud and data certifications, including Databricks.

    Course Outline : Download Course Outline

    • Get started with Azure Databricks
    • Identify Azure Databricks workloads.
    • Understand key concepts.
    • Data governance using Unity Catalog and Microsoft Purview
    • Lab - Explore Azure Databricks

    • Ingest data with Azure Databricks.
    • Data exploration tools in Azure Databricks.
    • Data analysis using DataFrame APIs.
    • Lab - Explore data with Azure Databricks

    • Get to know Spark.
    • Create a Spark cluster.
    • Use Spark in notebooks.
    • Use Spark to work with data files.
    • Visualize data.
    • Lab - Use Spark in Azure Databricks

    • Get started with Delta Lake.
    • Manage ACID transactions.
    • Implement schema enforcement.
    • Data versioning and time travel in Delta Lake.
    • Data integrity with Delta Lake.
    • Lab- Use Delta Lake in Azure Databricks

    • Explore Delta Live Tables.
    • Data ingestion and integration.
    • Real-time processing.
    • Lab - Create a data pipeline with Delta Live Tables.

    • What are Azure Databricks Workflows?.
    • Understand key components of Azure Databricks Workflows.
    • Explore the benefits of Azure Databricks Workflows.
    • Deploy workloads using Azure Databricks Workflows.
    • Lab - Create an Azure Databricks Workflow.

    Certification details:

    • Candidates who successfully complete the DP-3011 Microsoft Azure Applied Skills training are awarded a certificate of course completion.
    • Earning the Microsoft Azure DP-3011 Applied Skill Credential validates your ability to build and manage data analytics solutions using Azure Databricks.
    • In the DP-3011 Applied Skills course, you will learn how to design and implement scalable data analytics pipelines with Apache Spark and Delta Lake in Azure Databricks.
    • Applied Skills credentials can serve as a foundation to prepare for more specialized or role-based Azure certifications.  
    • Candidates also receive an official Microsoft credential upon passing the Microsoft Azure DP-3011 Applied Skills assessment.

    Click to Zoom

    Select Course date

    Loading Dates...
    Add to Wishlist

    Course ID: 21262

    Course Price at

    Loading price info...
    Enroll Now

    FAQs on DP 3011

    A Microsoft instructor-led training course called DP-3011 shows students how to use Azure Databricks to create and administer end-to-end data analytics applications. Workload orchestration, governance, data pipelines, Spark, and Delta Lake are all covered on a single platform.

    This course is ideal for: Data Engineers Data Analysts Data Scientists Those who want to use Apache Spark and Databricks to manage big data workflows on Azure.

    Yes. Learners should have: Basic knowledge of Azure services Experience with SQL and Python (or another programming language) Familiarity with data processing concepts (ETL, batch vs streaming, etc.) Recommended: Completion of DP-900: Azure Data Fundamentals

    After completing this course, learners will be able to: Use and manage Azure Databricks and Spark clusters Perform data ingestion, exploration, and transformation Build data pipelines using Delta Lake and Delta Live Tables Implement data governance using Unity Catalog Orchestrate production workloads with Databricks Workflows

    Not during official training sessions. Labs are typically run in a pre-provisioned environment. For self-study or practice outside the course, an Azure subscription with Databricks access is required.

    Yes. Azure Databricks is in high demand for big data and AI workloads. Professionals with solid Spark, Python, and Databricks skills can command 20% or higher salaries over traditional data engineers.

    Databricks: Spark-based, better for unstructured/semi-structured data, ML workloads, and streaming. Synapse: SQL-first, better for structured data and T-SQL queries at scale.

    Enquire Now