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Niraj Joshi

This course will teach you the data partitioning and sharding strategies in relational as well as non-relational cloud stores. Analyze data distribution before migration to Azure.

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This course will teach you the data partitioning and sharding strategies in relational as well as non-relational cloud stores. Analyze data distribution before migration to Azure.

Partitioning is an important strategy to segregate the data based on the partition key and distribute the data evenly across partitions for efficient querying and analysis.

In this course, Implement Partitioning with Azure, you’ll learn to apply efficient partitioning, sharding, and data distribution techniques over Azure Cloud Portal for specific services:

This course teaches the importance of partitioning, how to select a partition key, what Azure Synapse is, and MPP architecture of Azure Synapse.

Partitioning is the creation of one or more regions on secondary storage, so that each region can be managed separately.

Before taking this course, it would be beneficial to have an understanding of

.

Cloud stores or storage is a model of computer data storage where the digital data is stored in logistical pools, said to be on "the cloud".

Azure Synapse analytics is a limitless analytics service that brings together data integration, enterprise data warehousing, and big data analytics.

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What's inside

Syllabus

Course Overview
Partitioning in Non-relational Cloud Data Stores
Partitioning in Relational Cloud Data Stores
Partitioning in Azure Synapse
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines partitioning, which is standard in industry cloud technology
Teaches how to choose a partition key relevant to your own work
Helps learners develop partitioning, sharding, data distribution techniques
Taught by Niraj Joshi, who is recognized for their work in IT professionals training
Examines Azure Synapse, MPP architecture of Azure Synapse, which is highly relevant to cloud computing
Prerequisites may be required for this course that might add to the expense

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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 Implement Partitioning with Azure with these activities:
Review relational database concepts
Reviewing relational database concepts can solidify your understanding of the fundamentals that underpin data partitioning and sharding.
Browse courses on Relational Databases
Show steps
  • Review the main concepts of relational databases, such as tables, rows, columns, and relationships.
  • Practice writing SQL queries to retrieve and manipulate data from relational databases.
  • Identify the different types of database joins and when to use each type.
  • Understand the concept of database normalization and its importance in data management.
Participate in peer study groups or discussion forums
Engaging with peers can foster a collaborative learning environment, allowing you to share knowledge, clarify concepts, and gain diverse perspectives on data partitioning and sharding.
Browse courses on Data Partitioning
Show steps
  • Join online discussion forums or study groups dedicated to data partitioning and sharding.
  • Actively participate in discussions, sharing your insights and asking questions.
  • Collaborate with peers on projects or assignments related to data partitioning and sharding.
Review cloud storage and data partitioning concepts
Reviewing cloud storage and data partitioning concepts will provide a strong foundation for understanding the course content.
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Show steps
  • Read the syllabus and course overview.
  • Explore online resources and tutorials on cloud storage and data partitioning.
Ten other activities
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Follow tutorials on data partitioning and sharding
Guided tutorials can provide hands-on experience with data partitioning and sharding techniques, reinforcing your understanding of the concepts discussed in the course.
Browse courses on Data Partitioning
Show steps
  • Find tutorials that cover data partitioning and sharding in the context of relational or non-relational cloud data stores.
  • Follow the tutorials step-by-step, implementing the techniques in your own cloud environment.
  • Experiment with different partitioning and sharding strategies to understand the impact on data distribution and query performance.
Attend webinars and online meetups on data partitioning and Azure Synapse
Attending webinars and online meetups will provide opportunities to connect with experts and learn about the latest trends in data partitioning and Azure Synapse.
Browse courses on Azure Synapse
Show steps
  • Research upcoming webinars and online meetups.
  • Register for relevant events.
  • Attend the events and participate actively.
Attend industry events focused on data partitioning and sharding
Attending industry events can provide networking opportunities and exposure to the latest trends and best practices in data partitioning and sharding.
Browse courses on Data Partitioning
Show steps
  • Identify industry conferences or meetups that focus on data partitioning and sharding.
  • Attend the events and actively participate in discussions and networking sessions.
  • Connect with experts and practitioners in the field to learn from their experiences.
Practice partitioning data in Azure Synapse using T-SQL
Practicing partitioning data in Azure Synapse using T-SQL will reinforce the concepts learned in the course.
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Show steps
  • Set up an Azure Synapse environment.
  • Create a table and insert sample data.
  • Write T-SQL queries to partition the data.
  • Analyze the results and optimize the partitioning strategy.
Compile a collection of resources on data partitioning and sharding
Creating a compilation of resources can serve as a valuable reference for future projects and reinforce your understanding of data partitioning and sharding.
Browse courses on Data Partitioning
Show steps
  • Gather articles, tutorials, documentation, and other resources on data partitioning and sharding.
  • Organize the resources into a coherent collection, categorizing them by topic or use case.
  • Share the compilation with peers or contribute it to online communities for the benefit of others.
Participate in workshops on data partitioning and Azure Synapse
Participating in workshops on data partitioning and Azure Synapse will provide hands-on experience and in-depth knowledge.
Browse courses on Azure Synapse
Show steps
  • Identify reputable organizations that offer workshops.
  • Research the content and instructors of the workshops.
  • Register for and attend the workshops.
  • Actively participate in the exercises and discussions.
Design a data partitioning strategy for a real-world dataset
Designing a data partitioning strategy for a real-world dataset will apply the concepts learned in the course to a practical scenario.
Browse courses on Data Partitioning
Show steps
  • Choose a real-world dataset.
  • Analyze the dataset and identify potential partitioning keys.
  • Design a data partitioning strategy.
  • Document the partitioning strategy.
Mentor other students or aspiring data professionals on data partitioning and Azure Synapse
Mentoring others will reinforce the concepts learned in the course and enhance communication and leadership skills.
Browse courses on Azure Synapse
Show steps
  • Identify opportunities to mentor others.
  • Prepare materials and resources for mentoring sessions.
  • Meet with mentees regularly and provide guidance.
  • Provide feedback and support to mentees.
Follow tutorials on advanced data partitioning techniques in Azure Synapse
Following tutorials on advanced data partitioning techniques in Azure Synapse will expand knowledge and skills beyond the course content.
Browse courses on Azure Synapse
Show steps
  • Identify reputable sources for tutorials.
  • Select tutorials that align with interests and learning goals.
  • Follow the tutorials step-by-step.
  • Experiment with different techniques and configurations.
Contribute to open-source projects related to data partitioning or Azure Synapse
Contributing to open-source projects related to data partitioning or Azure Synapse will provide practical experience and enhance understanding of the technologies.
Browse courses on Azure Synapse
Show steps
  • Identify open-source projects related to data partitioning or Azure Synapse.
  • Review the project documentation and codebase.
  • Identify areas where contributions can be made.
  • Submit pull requests with proposed changes or improvements.
  • Collaborate with other contributors and maintainers.

Career center

Learners who complete Implement Partitioning with Azure will develop knowledge and skills that may be useful to these careers:
Data Engineer
A Data Engineer builds and maintains data pipelines and infrastructure. This course would be very useful to Data Engineers as it teaches the benefits of data partitioning, different partitioning strategies, and how to partition data efficiently in Azure. Additionally, the course provides guidance on choosing the right partition key, which is critical for effective data partitioning.
Cloud Data Engineer
A Cloud Data Engineer builds and manages data pipelines in the cloud. This course would be very useful to Cloud Data Engineers as it teaches partitioning strategies for relational and non-relational cloud data stores, which are important for designing efficient data pipelines. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale cloud data processing.
Data Warehouse Architect
A Data Warehouse Architect designs and manages data warehouses. This course would be very useful to Data Warehouse Architects as it teaches partitioning strategies for relational and non-relational cloud data stores, which are important for designing efficient data warehouses. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.
Big Data Engineer
A Big Data Engineer works with large datasets and builds data pipelines to process and analyze data. This course would be very useful to Big Data Engineers as it teaches partitioning strategies for relational and non-relational cloud data stores, which are important for designing efficient data pipelines. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data processing and analysis.
Data Integration Engineer
A Data Integration Engineer builds and maintains data pipelines that integrate data from multiple sources. This course would be very useful to Data Integration Engineers as it teaches partitioning strategies for relational and non-relational cloud data stores, which are important for designing efficient data pipelines. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data integration.
Cloud Solutions Architect
A Cloud Solutions Architect designs and manages cloud computing solutions. This course would be beneficial to Cloud Solutions Architects responsible for designing and implementing data solutions in the cloud. The course provides an overview of partitioning techniques for relational and non-relational cloud data stores. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.
Cloud Architect
A Cloud Architect designs and manages cloud computing systems. This course would be beneficial to Cloud Architects responsible for designing and implementing data solutions in the cloud. The course provides an overview of partitioning techniques for relational and non-relational cloud data stores. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.
Data Scientist
A Data Scientist uses data to build models and make predictions. This course would be beneficial to Data Scientists who are involved in working with large datasets stored in cloud data stores. The course teaches partitioning strategies that can help improve the performance of data science models. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data science.
Database Administrator
A Database Administrator manages and maintains databases. This course would be beneficial to Database Administrators responsible for designing and managing large-scale relational databases in the cloud. It provides an in-depth understanding of partitioning techniques and how to apply them to optimize database performance. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.
Database Developer
A Database Developer designs and develops databases. This course would be useful to Database Developers responsible for designing and developing large-scale relational databases in the cloud. It provides an in-depth understanding of partitioning techniques and how to apply them to optimize database performance. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.
Data Governance Analyst
A Data Governance Analyst develops and implements data governance policies and procedures. This course may be useful for Data Governance Analysts who are responsible for managing data in cloud data stores. The course teaches partitioning strategies that can help improve the security and compliance of data stored in the cloud. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data storage.
Business Intelligence Analyst
A Business Intelligence Analyst uses data to make informed business decisions. This course would be useful for Business Intelligence Analysts who are involved in working with large datasets stored in cloud data stores. The course teaches partitioning strategies that can help improve the performance of business intelligence queries. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale business intelligence.
Data Architect
A Data Architect designs, develops, and manages the architecture of data systems. This course may be useful to Data Architects as it teaches partitioning strategies for relational and non-relational cloud data stores, which are important for designing efficient data architectures. Additionally, the course covers partitioning in Azure Synapse, which is a popular cloud-based data warehouse solution.
Data Analyst
A Data Analyst analyzes data to identify trends and patterns. This course may be useful for Data Analysts who are involved in working with large datasets stored in cloud data stores. The course teaches partitioning strategies that can help improve the performance of data analysis queries. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data analysis.
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for Software Engineers who are involved in developing data-intensive applications. The course teaches partitioning strategies that can help improve the performance of data-intensive applications. Additionally, the course covers partitioning in Azure Synapse, which is a popular choice for large-scale data warehousing.

Reading list

We've selected seven 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 Implement Partitioning with Azure.
Provides a comprehensive overview of the principles, techniques, and challenges involved in designing and building data-intensive applications. It covers a wide range of topics, from data modeling and storage to scalability and reliability, and valuable resource for anyone looking to build robust and efficient data-driven systems.
Provides a comprehensive overview of cloud data management, including data partitioning and sharding. It good resource for anyone looking to learn more about this topic.
This classic book provides a comprehensive overview of data warehousing, including techniques for data partitioning and sharding. It valuable resource for anyone looking to design and implement a scalable and performant data warehouse.
Provides a comprehensive guide to optimizing MySQL performance, including techniques for data partitioning and sharding. It valuable resource for anyone looking to improve the performance of their MySQL databases.
Provides a comprehensive overview of big data analytics, including data partitioning and sharding. It good resource for anyone looking to learn more about this topic.
Provides a comprehensive overview of data management for modern business, including data partitioning and sharding. It good resource for anyone looking to learn more about this topic.
Provides a comprehensive overview of big data management, including data partitioning and sharding. It good resource for anyone looking to learn more about this topic.

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