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Henry Been
This course will teach you about core data concepts including the different types of data, databases, and workloads, and the differences between batch and streaming data.
Read more
This course will teach you about core data concepts including the different types of data, databases, and workloads, and the differences between batch and streaming data.
Read more
This course will teach you about core data concepts including the different types of data, databases, and workloads, and the differences between batch and streaming data.
Are you wondering how to get started in the field of data? Do you want to build a foundational understanding of types of data and data workloads? In this course, Getting Started with Azure Data Workloads, you’ll learn to differentiate between different types of data, databases, and data workloads. First, you’ll explore the difference between structured and unstructured data. Next, you’ll discover different types of databases and data workloads. Finally, you’ll learn how to differentiate between batch data and streaming data. When you’re finished with this course, you’ll be able to decide if a problem is best solved using batch data or streaming data, and you'll have the skills and knowledge to become a successful data engineer.
Register for this course and see more details by visiting:
OpenCourser.com/course/sydn1x/getting
What's inside
Syllabus
Course Overview
Types of Data, Databases, and Workloads
Batch Data and Streaming Data
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops a foundational understanding of different data types, databases, and workloads, which are core skills for data engineers
Taught by Henry Been, who are recognized for their work in data engineering
Covers core data concepts that are highly relevant in industry
Explores the difference between batch data and streaming data, which is standard in industry
Save this course
Save Getting Started with Azure Data Workloads to your list so you can find it easily later:
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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 Getting Started with Azure Data Workloads with these
activities:
Organize course resources and notes
Show steps
Enhance your understanding of course materials by organizing and reviewing notes, assignments, and other resources.
Show steps
-
Create a dedicated folder or notebook for course materials.
-
Organize resources by topic or module.
-
Summarize key concepts and insights from each resource.
Connect with experienced data engineers
Show steps
Gain valuable insights and guidance from experienced data engineers to accelerate your learning journey.
Show steps
-
Attend industry events or join online communities to connect with data engineers.
-
Reach out to potential mentors and express your interest in learning from them.
-
Schedule regular meetings or discussions to gain insights and advice.
Review Python programming basics
Show steps
Strengthen your Python programming skills to enhance your ability to work with and analyze data effectively.
Browse courses on
Python Programming
Show steps
-
Review Python syntax and data structures.
-
Practice writing Python code for data manipulation tasks.
-
Complete coding exercises on platforms like Codecademy or HackerRank.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete tutorials on data ingestion methods
Show steps
Gain hands-on experience with different data ingestion methods to enhance your understanding of data acquisition techniques.
Browse courses on
Data Ingestion
Show steps
-
Find tutorials on Azure Data Factory or similar tools.
-
Follow the tutorials to create data pipelines and ingest data from various sources.
-
Experiment with different data formats and ingestion methods.
Attend a workshop on data visualization techniques
Show steps
Expand your knowledge of data visualization techniques and best practices to effectively communicate insights from data.
Browse courses on
Data Visualization
Show steps
-
Find and register for a workshop on data visualization.
-
Attend the workshop and actively participate in discussions.
-
Apply the learned techniques to your own data analysis projects.
Solve data engineering challenges on coding platforms
Show steps
Enhance your problem-solving skills and deepen your understanding of data engineering concepts through coding challenges.
Browse courses on
Algorithm Design
Show steps
-
Find coding challenges related to data engineering on platforms like LeetCode or HackerRank.
-
Attempt to solve challenges involving data structures, algorithms, and data manipulation techniques.
-
Review solutions and learn from best practices.
Develop a data storage strategy for a real-world scenario
Show steps
Apply your knowledge of data storage options and design principles to create a practical data storage strategy.
Browse courses on
Data Architecture
Show steps
-
Identify a specific business scenario that requires data storage.
-
Analyze data requirements, including data volume, access patterns, and performance needs.
-
Evaluate different data storage options (e.g., relational databases, NoSQL databases, cloud storage).
-
Design a data storage architecture and create a detailed implementation plan.
Organize course resources and notes
Show steps
Enhance your understanding of course materials by organizing and reviewing notes, assignments, and other resources.
Show steps
Show steps
Show steps
- Create a dedicated folder or notebook for course materials.
- Organize resources by topic or module.
- Summarize key concepts and insights from each resource.
Connect with experienced data engineers
Show steps
Gain valuable insights and guidance from experienced data engineers to accelerate your learning journey.
Show steps
Show steps
Show steps
- Attend industry events or join online communities to connect with data engineers.
- Reach out to potential mentors and express your interest in learning from them.
- Schedule regular meetings or discussions to gain insights and advice.
Review Python programming basics
Show steps
Strengthen your Python programming skills to enhance your ability to work with and analyze data effectively.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review Python syntax and data structures.
- Practice writing Python code for data manipulation tasks.
- Complete coding exercises on platforms like Codecademy or HackerRank.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete tutorials on data ingestion methods
Show steps
Gain hands-on experience with different data ingestion methods to enhance your understanding of data acquisition techniques.
Browse courses on
Data Ingestion
Show steps
Show steps
Show steps
- Find tutorials on Azure Data Factory or similar tools.
- Follow the tutorials to create data pipelines and ingest data from various sources.
- Experiment with different data formats and ingestion methods.
Attend a workshop on data visualization techniques
Show steps
Expand your knowledge of data visualization techniques and best practices to effectively communicate insights from data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find and register for a workshop on data visualization.
- Attend the workshop and actively participate in discussions.
- Apply the learned techniques to your own data analysis projects.
Solve data engineering challenges on coding platforms
Show steps
Enhance your problem-solving skills and deepen your understanding of data engineering concepts through coding challenges.
Browse courses on
Algorithm Design
Show steps
Show steps
Show steps
- Find coding challenges related to data engineering on platforms like LeetCode or HackerRank.
- Attempt to solve challenges involving data structures, algorithms, and data manipulation techniques.
- Review solutions and learn from best practices.
Develop a data storage strategy for a real-world scenario
Show steps
Apply your knowledge of data storage options and design principles to create a practical data storage strategy.
Browse courses on
Data Architecture
Show steps
Show steps
Show steps
- Identify a specific business scenario that requires data storage.
- Analyze data requirements, including data volume, access patterns, and performance needs.
- Evaluate different data storage options (e.g., relational databases, NoSQL databases, cloud storage).
- Design a data storage architecture and create a detailed implementation plan.
Career center
Learners who complete Getting Started with Azure Data Workloads will develop knowledge and skills
that may be useful to these careers:
Data Architect
Data Architect
Data Architects design, manage, and implement data systems. They ensure that data is structured and organised in a way that meets business needs.
This course will help you build a foundation in data concepts that is necessary for a role as a Data Architect.
Data Engineer
Data Engineer
You may be interested in becoming a Data Engineer. Data Engineers are responsible for managing data within a company's infrastructure. They use data to solve problems, such as improving efficiency and automating processes.
This course may be helpful for you as it helps build a foundation for understanding data, databases, and workloads.
Data Analyst
Data Analyst
Those with a more business-oriented and communicative approach to data may find success as a Data Analyst. Data Analysts interpret data and share it with stakeholders.
This course will help you understand data and data workloads, which can help you succeed as a Data Analyst.
Database Administrator
Database Administrator
Database Administrators maintain and optimise data storage systems. This can include working with cloud-based and on-premise databases.
This course introduces foundational data concepts such as databases and data workloads. It may be useful as you begin your career as a Database Administrator.
Machine Learning Engineer
Machine Learning Engineer
Those with an interest in the intersection of data and software may find success as a Machine Learning Engineer. Machine Learning Engineers develop, implement, and maintain machine learning models.
This course can help you build a foundation for understanding real-world data applications, which can help you as a Machine Learning Engineer.
Data Scientist
Data Scientist
If you are drawn to a more analytical and mathematical career path in data, consider becoming a Data Scientist. Data Scientists use mathematical models to derive insights from data.
Taking this course may be useful for you because it will help you gain a foundational understanding of data concepts.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and build data warehouses, which are used to store and manage large amounts of data.
This course will help you understand data and data workloads, which can help you succeed as a Data Warehouse Architect.
Data Integration Engineer
Data Integration Engineer
Data Integration Engineers build and manage the infrastructure that connects and integrates data from multiple sources.
This course will help you build a foundation for understanding data and data workloads, which can be helpful for a role as a Data Integration Engineer.
Software Engineer
Software Engineer
If you are interested in a career as a software engineer with a focus on data-intensive applications, you may be interested in becoming a Software Engineer.
This course can help you understand data and data workloads, which can be useful for building data applications.
Data Management Consultant
Data Management Consultant
This course can help you develop a foundation for data concepts that may be useful if you are looking to enter the field of data management consulting.
Business Analyst
Business Analyst
If you are interested in a career that focuses on analysing business data and developing solutions, consider becoming a Business Analyst.
This course can help you build a foundation in data concepts, including types of data and data workloads.
Cloud Architect
Cloud Architect
Cloud Architects who work with data-intensive applications could benefit from this course. This course can help build your understanding of data concepts.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts ensure that an organisation's data usage complies with regulations and standards. They also develop policies and procedures for data management.
This course may be helpful for building a foundation in data concepts.
For more career information including salaries, visit:
OpenCourser.com/course/sydn1x/getting
Reading list
We've selected eight 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
Getting Started with Azure Data Workloads.
Provides a comprehensive textbook-level treatment of database systems concepts and technologies.
Provides a practical introduction to using Pandas for data analysis and manipulation in Python.
Save
Provides a broad overview of data mining techniques and their applications.
Provides a comprehensive guide to Cassandra, a wide-column, distributed database system.
Save
Introduces the Spark framework and its use for large-scale data processing and analysis.
Covers the use of the Hadoop MapReduce framework and related tools for data-intensive text processing.
Offers a beginner-friendly introduction to SQL, the standard language for accessing and manipulating relational databases.
Offers a non-technical, easy-to-understand introduction to data management concepts and best practices.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sydn1x/getting
Share
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Time
42 hours
Level
Introductory
Via
Pluralsight
Instructor
Henry Been
Language
English
Good to know
Develops a foundational understanding of different data types, databases, and workloads, which are core skills for data engineers
Taught by Henry Been, who are recognized for their work in data engineering
Covers core data concepts that are highly relevant in industry
Explores the difference between batch data and streaming data, which is standard in industry
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