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Overview

This course explores how to use Databricks and Apache Spark on Azure to take data projects from exploration to production. You’ll learn how to ingest, transform, and analyze large-scale datasets with Spark Data Frames, Spark SQL, and PySpark, while also building confidence in managing distributed data processing. Along the way, you’ll get hands-on with the Databricks workspace—navigating clusters and creating and optimizing Delta tables.   You’ll also dive into data engineering practices, including designing ETL pipelines, handling schema evolution, and enforcing data quality. The course then moves into orchestration, showing you how to automate and manage workloads with Lake flow Jobs and pipelines. To round things out, you’ll explore governance and security capabilities such as Unity Catalog and Purview integration, ensuring you can work with data in a secure, well-managed, and production-ready environment.
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What You'll Learn

  • Use the Azure Databricks workspace to ingest, transform, and analyse large-scale datasets with Spark DataFrames, Spark SQL and PySpark.
  • Navigate and configure Spark clusters and Delta tables (including schema enforcement, versioning and time-travel).
  • Design and build production-ready ETL/ELT data pipelines using declarative constructs (e.g., Delta Live Tables) and orchestration mechanisms (e.g., Lakeflow Jobs & pipelines).
  • Implement governance, security and management features (such as Unity Catalog and integration with Microsoft Purview) to ensure your data-lakehouse solution is production-ready.

Who Should Attend

Before taking this course, learners should already be comfortable with the fundamentals of Python and SQL. This includes being able to write simple Python scripts and work with common data structures, as well as writing SQL queries to filter, join, and aggregate data. A basic understanding of common file formats such as CSV, JSON, or Parquet will also help when working with datasets. In addition, familiarity with the Azure portal and core services like Azure Storage is important, along with a general awareness of data concepts such as batch versus streaming processing and structured versus unstructured data. While not mandatory, prior exposure to big data frameworks like Spark, and experience working with Jupyter notebooks, can make the transition to Databricks smoother.
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Prerequisites

  • Before starting this, you should already be comfortable with the fundamentals of Python and SQL. This includes being able to write simple Python scripts and work with common data structures, as well as writing SQL queries to filter, join, and aggregate data. A basic understanding of common file formats such as CSV, JSON, or Parquet will also help when working with datasets.
  • In addition, familiarity with the Azure portal and core services like Azure Storage is important, along with a general awareness of data concepts such as batch versus streaming processing and structured versus unstructured data. While not mandatory, prior exposure to big data frameworks like Spark, and experience working with Jupyter notebooks, can make the transition to Databricks smoother.

Learning Journey

Coming Soon...

1. Explore Azure Databricks

Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.

2. Perform data analysis with Azure Databricks

Learn how to perform data analysis using Azure Databricks. Explore various data ingestion methods and how to integrate data from sources like Azure Data Lake and Azure SQL Database. This module guides you through using collaborative notebooks to perform exploratory data analysis (EDA), so you can visualize, manipulate, and examine data to uncover patterns, anomalies, and correlations.

3. Use Apache Spark in Azure Databricks

Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.

4. Manage data with Delta Lake

Delta Lake is a data management solution in Azure Databricks providing features including ACID transactions, schema enforcement, and time travel ensuring data consistency, integrity, and versioning capabilities.

5. Build data pipelines with Delta Live Tables

Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks

6. Deploy workloads with Azure Databricks Workflows

Deploying workloads with Azure Databricks Workflows involves orchestrating and automating complex data processing pipelines, machine learning workflows, and analytics tasks. In this module, you learn how to deploy workloads with Databricks Workflows.

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Frequently Asked Questions (FAQs)

  • Why get Microsoft certified?

    Microsoft certifications validate your skills and expertise in Microsoft technologies and solutions, demonstrating your ability to design, implement, and manage cutting-edge technologies.

    These certifications are globally recognized and highly sought after by employers, as they signify your proficiency in using Microsoft products and services to drive innovation and solve business challenges.

    Microsoft-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    Microsoft certification exams are designed to assess your knowledge and skills in specific Microsoft technologies and solutions.

    Exams typically consist of multiple-choice, multiple-select, and case study questions, and some may include lab simulations to evaluate your practical skills.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Microsoft certification valid for?

    Most Microsoft role-based and specialty certifications are valid for one year from the date of passing the exam.

    To maintain your certification, you will need to renew it annually by passing a free online assessment on Microsoft Learn.

    However, Microsoft Applied Skills credentials and Fundamentals certifications do not expire.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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