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Data Literacy

Essentials of Azure Databricks

This course will teach you about the different components that make up Azure DataBricks. This is done by going through the different capabilities and how they help improve your data estate.

There are different solutions data professionals are trying to create and it is important to understand what tool is right for the job. In this course, Data Literacy: Essential of Azure DataBricks, you’ll learn about the different components that make up Azure DataBricks. First, you’ll explore its history and its relationship to common data solutions like Big Data, Machine Learning and Spark. Next, you’ll discover what the Azure DataBricks workspace is and how data can be ingested into it. Finally, you’ll learn about the list of capabilities within the workspace and how it integrates with other data tools. When you’re finished with this course, you’ll have the skills and knowledge of Azure DataBricks as a tool to create Big Data and Machine Learning Solutions.

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What's inside

Syllabus

Course Overview

Key Components of Azure Databricks

Capabilities of Azure Databricks

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Useful for building essential knowledge within Azure's ecosystem and data management and analysis field

Provides a broad understanding of Microsoft's Azure DataBricks suite and the use cases it supports

Introduces the common data solutions used in industry such as Big Data, Machine Learning and Spark technologies

May complement courses focused on the development and implementation of data science solutions

The target student is assumed to have an understanding of data science fundamentals, including big data and machine learning concepts

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Literacy: Essentials of Azure Databricks with these activities:

Follow tutorials on Azure Databricks capabilities

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Provides hands-on experience and reinforces understanding of various Azure Databricks capabilities through guided tutorials.

Browse courses on Data Ingestion

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Search for Azure Databricks tutorials
Choose a tutorial that aligns with learning objectives
Follow the tutorial steps and complete the exercises
Troubleshoot any issues encountered (optional)

Complete Azure Databricks exercises

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Provides opportunities to apply knowledge and develop proficiency in using Azure Databricks through practical exercises.

Browse courses on Data Ingestion

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Find Azure Databricks exercises online or in the course materials
Set aside dedicated time for completing the exercises
Work through the exercises step-by-step
Review solutions and identify areas for improvement (optional)

Build a data pipeline using Azure Databricks

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Challenges students to apply their knowledge and skills by building a complete data pipeline using Azure Databricks, reinforcing understanding of the entire data processing workflow.

Browse courses on Data Pipeline

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Define the data sources and destination
Design the data pipeline architecture
Implement the data pipeline using Azure Databricks
Test and validate the data pipeline
Document the data pipeline (optional)

Two other activities

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Mentor junior data professionals on Azure Databricks

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Enhances understanding and retention by providing opportunities to teach others and reinforce concepts while supporting the growth of junior professionals.

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Identify opportunities to mentor junior data professionals
Share knowledge and experience on Azure Databricks
Guide mentees through Azure Databricks concepts and practices
Provide feedback and support to enhance learning outcomes

Contribute to open-source Azure Databricks projects

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Provides real-world experience and fosters collaboration by encouraging contributions to the Azure Databricks open-source community, deepening understanding and showcasing practical applications.

Browse courses on Open Source

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Identify open-source Azure Databricks projects
Review project documentation and codebase
Identify areas for potential contributions
Submit bug reports or feature requests (optional)
Contribute code or documentation to the project

Career center

Learners who complete Data Literacy: Essentials of Azure Databricks will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist uses data to build models that can make predictions and recommendations. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to build and deploy data science models more efficiently.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models to solve a variety of problems, including fraud detection, customer churn prediction, and image recognition. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to build and deploy machine learning models more efficiently.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

A Business Analyst analyzes business processes and data to identify areas for improvement. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to analyze business processes and data more efficiently.

See salaries and explore the career path for Business Analyst

Data Architect

A Data Architect designs and implements data management solutions. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to design and implement data management solutions more effectively.

See salaries and explore the career path for Data Architect

Software Engineer

A Software Engineer designs, develops, and maintains software applications. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to build and deploy software applications that can process and analyze large amounts of data.

See salaries and explore the career path for Software Engineer

Data Analyst

A Data Analyst collects, analyzes, and interprets data to help organizations make informed decisions. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the different components of Azure Databricks and how they can be used to ingest, process, and analyze data. This knowledge can help learners to become more efficient in their data analysis work.

See salaries and explore the career path for Data Analyst

Database Administrator

A Database Administrator manages and maintains databases. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to manage and maintain databases more efficiently.

See salaries and explore the career path for Database Administrator

Data Engineer

A Data Engineer builds and maintains data pipelines and databases. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to build and manage data pipelines and databases more efficiently.

See salaries and explore the career path for Data Engineer

Cloud Architect

A Cloud Architect designs and implements cloud-based solutions. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to design and implement cloud-based solutions more effectively.

See salaries and explore the career path for Cloud Architect

Data Science Manager

A Data Science Manager leads and manages a team of data scientists. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to lead and manage a team of data scientists more effectively.

See salaries and explore the career path for Data Science Manager

Data Warehouse Architect

A Data Warehouse Architect designs and implements data warehouse solutions. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to design and implement data warehouse solutions more effectively.

See salaries and explore the career path for Data Warehouse Architect

Big Data Engineer

A Big Data Engineer designs and builds systems to process and analyze large amounts of data. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to build and manage big data systems more efficiently.

See salaries and explore the career path for Big Data Engineer

Data Analytics Manager

A Data Analytics Manager leads and manages a team of data analysts. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to lead and manage a team of data analysts more effectively.

See salaries and explore the career path for Data Analytics Manager

Cloud Computing Architect

A Cloud Computing Architect designs and implements cloud-based solutions. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to design and implement cloud-based solutions more effectively.

See salaries and explore the career path for Cloud Computing Architect

Big Data Manager

A Big Data Manager leads and manages a team of big data engineers. The course, Data Literacy: Essentials of Azure Databricks, may be useful for this role because it teaches learners about the capabilities of Azure Databricks, a cloud-based platform for big data and machine learning. This knowledge can help learners to lead and manage a team of big data engineers more effectively.

See salaries and explore the career path for Big Data Manager

Reading list

We've selected three books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Literacy: Essentials of Azure Databricks.

Spark: The Definitive Guide

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Comprehensive guide to Apache Spark, the open-source cluster-computing framework used in Azure Data Bricks. It covers the details of Spark's architecture, programming model, and advanced topics.

Spark: The Definitive Guide

Paperback

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Spark: The Definitive Guide

Kindle Edition

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Generative AI in Practice

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Provides a solid foundation in data science concepts and techniques, beneficial for learners seeking a broader understanding of the field.

Generative AI in Practice: 100+ Amazing Ways...

Hardcover

Generative AI in Practice: 100+ Amazing Ways...

Kindle Edition

Data Science from Scratch

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Introduces the fundamental concepts of data science, including data wrangling, analysis, and visualization. It uses Python and R code examples and good starting point for understanding the concepts used in Azure Data Bricks.

Data Science from Scratch: First Principles with...

Paperback

Data Science from Scratch: First Principles with...

Kindle Edition

Data Science from Scratch: First Principles with...

Paperback

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Time

23 hours

Level

Introductory

Via

Pluralsight

Instructor

Dayo Bamikole

Language

English

Good to know

Useful for building essential knowledge within Azure's ecosystem and data management and analysis field

Provides a broad understanding of Microsoft's Azure DataBricks suite and the use cases it supports

Introduces the common data solutions used in industry such as Big Data, Machine Learning and Spark technologies

May complement courses focused on the development and implementation of data science solutions

The target student is assumed to have an understanding of data science fundamentals, including big data and machine learning concepts

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