Implementing a Data Analytics Solution with Azure Databricks (DP-3011)

Course 8685

Duration: 1 day
Language: English
Level: Intermediate

Unlock the potential of Azure Databricks with our intermediate-level course designed for data professionals, including Data Engineers and Data Scientists. Dive into the realm of Apache Spark and master the utilisation of powerful clusters on the Azure Databricks platform to tackle large-scale data engineering tasks in the cloud. Whether you're optimising data pipelines, building machine learning models, or analysing vast datasets, this course equips you with the skills and insights needed to excel in today's data-driven world.

Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Delivery Methods

In-Person
Online
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Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Training Information

In this course, you will:

Gain hands-on experience in harnessing many of the capabilities of Azure Databricks for data engineering tasks.
Enhance your proficiency in Apache Spark, a leading big data processing framework, and leverage it effectively in the cloud environment.
Learn best practices for optimising data workflows and pipelines, ensuring efficiency and scalability.
Acquire the skills to build and deploy advanced machine learning models using Azure Databricks, empowering you to extract actionable insights from your data.

Training Prerequisites

None.

Certification Information

Helps prepare for Exam DP-203: Data Engineering on Microsoft Azure

Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Training Outline

Explore Azure Databricks

Get started with Azure Databricks
Identify Azure Databricks workloads
Understand key concepts

Use Apache Spark in Azure Databricks

Get to know Spark
Create a Spark cluster
Use Spark in notebooks
Use Spark to work with data files
Visualise data

Use Delta Lake in Azure Databricks

Get Started with Delta Lake
Create Delta Lake tables
Create and query catalog tables
Use Delta Lake for streaming data

Use SQL Warehouses in Azure Databricks

Get started with SQL Warehouses
Create databases and tables
Create queries and dashboards

Run Azure Databricks Notebooks with Azure Data Factory

Understand Azure Databricks notebooks and pipelines
Create a linked service for Azure Databricks
Use a Notebook activity in a pipeline
Use parameters in a notebook

Get This Course 9 170 kr

1-Day Instructor-Led Training
Hands-On Labs
Microsoft Official Content
After-Course Instructor Coaching Included
Available for Private Team Training

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mar 12 10:00 - 17:30 CET

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mar 18 14:00 - 21:30 CET

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jun 11 9:00 - 16:30 CEST

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jun 11 10:00 - 17:30 CEST

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Implementing a Data Analytics Solution with Azure Databricks (DP-3011) FAQs

No prior experience is required. This course is suitable for both data engineering and data science professionals looking to enhance their skills with Azure Databricks.

Absolutely! Through hands-on exercises and projects, you'll gain practical experience in harnessing Azure Databricks for various data engineering tasks, including optimising data pipelines and building machine learning models.

This course not only covers key concepts and functionalities of Azure Databricks but also emphasises best practices for optimising data workflows and pipelines, ensuring you're equipped to handle real-world data challenges efficiently and effectively.