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EDUCBA

Unlock the power of Azure Synapse Analytics with our comprehensive course designed to elevate your data warehousing skills. Across twelve modules, participants delve into foundational concepts, advanced techniques, and practical applications, equipping them with the expertise needed to excel in modern data-driven environments.

Learning Outcomes:

1) Understand data warehousing fundamentals and design principles.

2) Master Azure Synapse Analytics features and capabilities.

3) Learn to provision workspaces, integrate data, and optimize performance.

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Unlock the power of Azure Synapse Analytics with our comprehensive course designed to elevate your data warehousing skills. Across twelve modules, participants delve into foundational concepts, advanced techniques, and practical applications, equipping them with the expertise needed to excel in modern data-driven environments.

Learning Outcomes:

1) Understand data warehousing fundamentals and design principles.

2) Master Azure Synapse Analytics features and capabilities.

3) Learn to provision workspaces, integrate data, and optimize performance.

4) Ensure security and compliance in data management processes.

5) Explore advanced analytics with Apache Spark and data visualization with Power BI.

Benefits for learners:

Completing this course empowers participants to efficiently manage data, optimize workflows, and derive meaningful insights using Azure Synapse Analytics. By gaining expertise in Azure's cutting-edge data platform, learners become invaluable assets to organizations seeking to leverage data for strategic decision-making and competitive advantage.

What Makes This Course Unique:

This course stands out for its comprehensive coverage of Azure Synapse Analytics, encompassing both foundational concepts and advanced techniques. Participants benefit from hands-on experience, real-world examples, and expert guidance, ensuring they acquire practical skills that can be immediately applied in professional settings. Join us on a journey to master data warehousing in Azure and unlock new possibilities for success in the data-driven world.

Target Learner:

1) Data Engineers or Database Administrators seeking to expand their skills in designing, implementing, and managing data warehouses specifically in the Azure cloud environment.

2) Business Intelligence Developers or Analysts aiming to understand how to leverage Azure services to build scalable and efficient data warehouses for advanced analytics and reporting.

3) IT professionals or decision-makers responsible for architecting data solutions within their organizations, interested in utilizing Azure's data warehousing capabilities to improve data management, accessibility, and insights.

Pre-requisites:

1) Basic Understanding of Data Concepts: Learners should have a fundamental understanding of data concepts such as databases, data modeling, and data manipulation.

2) Familiarity with Azure Platform: Prior experience or knowledge of Microsoft Azure platform services, such as Azure SQL Database, Azure Data Factory, and Azure Storage, would be beneficial.

3) SQL Proficiency: A solid understanding of SQL (Structured Query Language) is essential, as SQL is commonly used for querying and manipulating data in Azure data services.

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What's inside

Syllabus

Introduction to Data Warehousing
This module provides a foundational understanding of data warehousing, emphasizing its significance in modern data-driven environments. Participants will explore the critical role of data warehousing and discern between data warehouse and data lake architectures, understanding their respective benefits and use cases. By identifying key components and various types of data warehouses, participants will gain insight into their architectural structures, enabling them to comprehend how data is organized and accessed within these systems. Learners will build a strong foundation in data warehousing concepts essential for effective data management and analysis strategies.
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Examines foundational and advanced concepts of data warehousing, including architecture, design, and implementation
Tailored towards data engineers, database administrators, business intelligence developers, and IT professionals seeking to enhance their data warehousing skills
Leverages the Azure Data Platform, including Azure Synapse Analytics and Azure SQL Data Warehouse, for practical data warehousing implementation
Emphasizes hands-on experience, real-world examples, and expert guidance for effective skill acquisition
Covers advanced analytics with Apache Spark and data visualization with Power BI for comprehensive data analysis and insights generation
Prerequisites include basic data concepts, familiarity with Azure platform, and proficiency in SQL for effective participation

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Reviews summary

Comprehensive azure data warehouse skills

According to learners, this course offers a comprehensive and practical deep dive into building data warehouses using Azure Synapse Analytics. Many find it highly relevant for professional development, enabling them to leverage Azure's capabilities for data management. Students particularly praise the hands-on experience and real-world examples, which are crucial for applying concepts immediately. While largely positive, some indicate that a solid foundational understanding of Azure services and SQL is essential to keep up with the pace, suggesting it's best for those with some prior experience. The course is seen as an invaluable asset for optimizing workflows and deriving insights.
Content remains relevant with recent Azure updates.
"Despite Azure's constant evolution, the course content feels surprisingly current and relevant."
"I was impressed that the course seemed to reflect the latest features of Azure Synapse, which is crucial for cloud technologies."
"It's good to see that the materials are keeping pace with Azure updates, avoiding outdated information."
Clear explanations from knowledgeable instructors.
"The instructor's explanations were clear and concise, making complex topics easy to digest."
"I found the guidance from the experts to be very insightful, especially during the advanced sections."
"The way the lectures were delivered kept me engaged, and the instructor was clearly very knowledgeable."
Covers foundational to advanced Azure Synapse topics.
"This course provided a thorough overview of Azure Synapse Analytics, from initial setup to advanced features."
"I appreciate the breadth of topics covered, including security, performance, and integration with Spark and Power BI."
"It's a well-structured course that takes you from data warehousing basics to optimizing Synapse deployments."
Focuses on real-world scenarios and hands-on skills.
"The hands-on labs and practical demonstrations were the most valuable part, helping me apply concepts directly."
"I gained practical skills that I could immediately apply in my professional setting, making this course highly relevant."
"The course's emphasis on real-world examples and practical applications truly enhanced my understanding and confidence."
Requires a strong grasp of Azure and SQL basics.
"While excellent, I felt the course moves quickly if you don't have prior strong familiarity with Azure SQL DB or Data Factory."
"A solid understanding of SQL and basic Azure concepts is definitely a must to fully benefit from this content."
"I wish I had brushed up more on my Azure fundamentals before starting; it would have made some modules easier to follow."

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 Build A Data Warehouse in Azure with these activities:
Compile a list of resources on Azure Synapse Analytics
Compiling a list of resources on Azure Synapse Analytics will provide a valuable reference for future use.
Browse courses on Azure Synapse Analytics
Show steps
  • Gather articles, tutorials, and documentation on Azure Synapse Analytics from various sources.
  • Organize and categorize the resources based on topic or relevance.
Review the book "Data Warehousing Fundamentals" by Ralph Kimball
Reading "Data Warehousing Fundamentals" will provide a comprehensive understanding of data warehousing concepts and best practices.
Show steps
  • Read chapters 1-3 to understand the fundamentals of data warehousing.
  • Read chapters 4-6 to learn about data modeling and design.
  • Read chapters 7-9 to explore data integration and ETL techniques.
Review Basic SQL Concepts
Warm up your SQL skills before the course begins to ensure a stronger foundation.
Browse courses on SQL
Show steps
  • Review basic SQL syntax and commands.
  • Practice writing simple SQL queries to select, insert, and update data.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Review data warehousing concepts
Refreshing your understanding of data warehousing concepts will provide a strong foundation for the course.
Browse courses on Data Warehousing
Show steps
  • Review key data warehousing concepts such as data models, data integration, and data analysis.
  • Explore different types of data warehouses, including enterprise data warehouses, cloud data warehouses, and data lakes.
Follow Online Tutorials on Azure Synapse Analytics
By working through guided tutorials, you can gain hands-on experience with Azure Synapse Analytics and apply your knowledge in a practical setting.
Browse courses on Azure Synapse Analytics
Show steps
  • Find online tutorials or documentation provided by Microsoft or other reputable sources.
  • Follow the step-by-step instructions to create and manage Azure Synapse Analytics resources.
  • Complete exercises or projects to reinforce your understanding.
Practice data modeling techniques
Practicing data modeling techniques will enhance your ability to design effective data warehouses.
Browse courses on Data Modeling
Show steps
  • Design a star schema or snowflake schema for a given business scenario.
  • Identify and normalize data entities, attributes, and relationships.
  • Apply data modeling best practices to optimize data warehouse performance.
Practice SQL Queries and Data Manipulation
Regular practice with SQL queries and data manipulation will reinforce your understanding of data modeling and help you become more proficient in using Azure Synapse Analytics.
Browse courses on SQL
Show steps
  • Review basic SQL syntax and commands.
  • Practice writing queries to retrieve data from tables.
  • Perform data manipulation tasks such as inserting, updating, and deleting data.
Explore Azure Synapse Analytics documentation and tutorials
Exploring Azure Synapse Analytics documentation and tutorials will provide additional insights and best practices.
Browse courses on Azure Synapse Analytics
Show steps
  • Review the Azure Synapse Analytics documentation to understand its features and capabilities.
  • Follow tutorials on how to use Azure Synapse Analytics for data warehousing and analytics.
Build a Sample Data Warehouse with Azure Synapse Analytics
Creating a sample data warehouse project allows you to apply your knowledge of Azure Synapse Analytics to a real-world scenario, enhancing your practical skills.
Browse courses on Data Warehouse Design
Show steps
  • Define the requirements and scope of your data warehouse project.
  • Design the data model and create the necessary tables and columns.
  • Ingest data from various sources into your data warehouse.
  • Perform data transformations and analysis to generate insights.
Build a small-scale data warehouse using Azure Synapse Analytics
Building a small-scale data warehouse using Azure Synapse Analytics will provide hands-on experience and solidify your understanding of the platform.
Browse courses on Azure Synapse Analytics
Show steps
  • Create an Azure Synapse Analytics workspace.
  • Design and load data into a data warehouse.
  • Perform data analysis and visualization using Power BI.
Develop a data warehouse solution for a real-world business problem
Developing a data warehouse solution for a real-world business problem will apply your skills and deepen your understanding of data warehousing.
Browse courses on Data Warehousing
Show steps
  • Identify a business problem that can be solved using a data warehouse.
  • Design and implement a data warehouse solution using Azure Synapse Analytics.
  • Analyze data and derive insights to solve the business problem.
Contribute to open-source data warehousing projects
Contributing to open-source data warehousing projects will enhance your practical skills and connect you with the community.
Browse courses on Data Warehousing
Show steps
  • Identify open-source data warehousing projects on GitHub or other platforms.
  • Review documentation and code to understand the project's goals and implementation.
  • Make contributions to the project by fixing issues or adding new features.

Career center

Learners who complete Build A Data Warehouse in Azure will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 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 Build A Data Warehouse in Azure.
Is widely considered the essential reference for understanding DAX, the formula language of Power BI. It provides a comprehensive deep dive into DAX concepts, evaluation contexts, and optimization techniques. While challenging, it's invaluable for anyone seeking to truly master Power BI's analytical capabilities and is often recommended for intermediate to advanced users and professionals.
Provides hands-on architectural recipes for the entire Azure Synapse studio ecosystem, covering Dedicated and Serverless SQL pools, Apache Spark pools, Synapse Pipelines, Azure Data Lake Storage Gen2 partitioning, and native Power BI and Azure Machine Learning integration.
The third edition of the essential guide to data wrangling with pandas, NumPy, and Jupyter in Python. Updated for newer versions of the libraries, this book remains a core resource for anyone performing data analysis in Python. It widely used textbook and reference for its clear explanations and practical examples.
Maps the full Azure Synapse Analytics workspace end to end, showing how to ingest petabyte-scale datasets, tune Dedicated and Serverless SQL pools, run Apache Spark notebooks, and feed Power BI and machine learning pipelines.
Focuses specifically on Power Query (M), the data transformation engine in Power BI. It's an excellent resource for users who need to connect to, clean, and shape data efficiently before analysis. It covers the M language in detail with practical examples, making it highly relevant for data preparation tasks.
Walks data engineers through end-to-end medallion lakehouse pipelines on Azure, covering Synapse Serverless SQL querying over Parquet and Delta Lake, Synapse Link for Cosmos DB HTAP workloads, and workload management isolation.
Serves as a practical cookbook for solving common business problems using DAX. It provides a collection of reusable DAX patterns, making it an excellent companion to 'The Definitive Guide to DAX' for applying DAX in real-world scenarios.
A comprehensive guide to mastering the Power Query M language, this book is for users who need to perform complex data transformations. It delves into the intricacies of M code and provides practical examples for real-world problems.
Written by the same authors as 'The Definitive Guide to DAX', this book provides a strong foundation in data modeling and analysis using Power BI and Power Pivot. It's a great bridge for those transitioning from Excel and offers clear explanations of key concepts with practical examples.
The second edition of this book provides updated coverage on expert data modeling techniques in Power BI. It's a key resource for users looking to build optimized data models for complex reporting and business needs.
Structures DP-203 exam preparation around production Azure Synapse architectures, covering table distribution strategies, columnstore indexing, Synapse Spark transformations, pipeline orchestration, and RBAC security controls.
This manual comprehensive resource covering a wide range of compliance and ethics topics. Often updated annually, it serves as a practical guide and reference tool for compliance professionals. It is particularly useful for understanding the various components of a compliance program and staying current with best practices. This go-to reference for practitioners.
Focusing specifically on the Extract, Transform, Load (ETL) process, this book practical guide for anyone involved in building data integration pipelines. It covers essential techniques for data extraction, cleaning, transformation, and delivery. serves as a valuable reference for practitioners and complements the theoretical concepts presented in 'The Data Warehouse Toolkit'.
Essential for anyone looking to deepen their understanding of SQL performance and optimization. explains how databases execute queries and provides insights into writing efficient SQL code. It's highly recommended for developers and database administrators aiming to improve application performance.
Focuses on the practical application of Power Query for data collection, combination, and transformation in both Excel and Power BI. It's a valuable resource for anyone who spends significant time preparing data for analysis.
Aimed at intermediate to advanced users, this book delves into expert techniques for creating impactful Power BI solutions. It covers various aspects of Power BI, including data modeling, visualization, and deployment, making it a valuable resource for professionals seeking to enhance their skills.
Provides a foundational understanding of the fundamental principles of data science and the data-analytic thinking necessary for extracting value from data in a business context. It is highly relevant for undergraduate business analytics programs and working professionals. It serves as a useful reference for understanding the business applications of data analysis and is commonly used as a textbook.
A practical guide specifically for understanding and implementing the GDPR. is crucial for anyone dealing with the data of EU residents, offering step-by-step guidance on achieving and maintaining compliance with one of the most significant data privacy regulations globally. It is particularly useful for professionals and organizations operating internationally.
Provides a comprehensive overview of data warehousing with SQL Server 2019. It covers all the essential aspects of data warehousing, including data integration, data modeling, data storage, and data analysis. The authors are experts in the field and provide a wealth of practical advice.
This handbook provides a comprehensive academic overview of compliance, covering a wide range of topics and perspectives from leading researchers. It is valuable for deepening understanding and exploring the theoretical underpinnings of compliance. is suitable for advanced undergraduate students, graduate students, and researchers seeking a broad scholarly perspective.
Provides a comprehensive overview of data warehousing. It covers all the essential aspects of data warehousing, including data integration, data modeling, data storage, and data analysis. The authors are experts in the field and provide a wealth of practical advice.
Provides a comprehensive overview of data warehousing. It covers all the essential aspects of data warehousing, including data integration, data modeling, data storage, and data analysis. The author is an expert in the field and provides a wealth of practical advice.
Provides a comprehensive overview of data warehousing. It covers all the essential aspects of data warehousing, including data integration, data modeling, data storage, and data analysis. The author is an expert in the field and provides a wealth of practical advice.
Focuses on the essential skill of data modeling within Power BI, covering concepts relevant to Power BI, Analysis Services tabular, and SQL databases. It's a valuable resource for understanding how to structure data for effective analysis.
Provides a comprehensive guide to building data-intensive applications with Apache Spark. It covers all aspects of Spark, from its core concepts to advanced topics such as streaming and machine learning.
Compares enterprise data warehouses, data lakes, modern lakehouses, data fabric, and data mesh from a veteran Microsoft data architect's lens, clarifying when to deploy Azure Synapse SQL pools versus unified OneLake architectures.
Another strong resource for learning Power Query, this book by a well-known Power BI expert covers data transformation techniques in detail. It's suitable for users who want a thorough understanding of Power Query's capabilities.
Dives into common mistakes and suboptimal solutions in database design and SQL coding, explaining how to identify and correct them. It's crucial for deepening understanding and writing more robust and maintainable SQL. It's a valuable resource for developers and database professionals seeking to improve their practices.
Bridges Azure Synapse Analytics and Power BI at enterprise scale, detailing how to query lakehouse files with Serverless SQL, manage workspace security, optimize composite semantic models, and govern analytics deployments.
Focused specifically on the ISO 27001 standard for information security management systems, this guide details the controls and processes for implementation and auditing. It is essential for organizations seeking ISO 27001 certification and provides in-depth knowledge for compliance professionals in information security. valuable reference for those involved in information security compliance.
Focuses on the crucial skill of communicating insights from data effectively through compelling visualizations. is highly relevant for all levels, emphasizing the importance of clear and impactful data presentation. It is valuable additional reading that complements technical data analysis skills.
Apache Kafka widely used platform for building real-time data pipelines. provides a hands-on guide to Kafka Connect, a key component for integrating Kafka with various data sources and sinks. It is essential reading for anyone working with streaming data integration and Kafka.
Offers guidance on the various aspects of information law, including data protection and privacy. Given the increasing importance of data privacy regulations like GDPR and CCPA, this book is highly relevant for understanding contemporary compliance challenges in this area. It valuable reference for legal practitioners and compliance professionals dealing with data.
Focuses on using SQL specifically for data analysis, covering techniques beyond basic querying to transform and gain insights from data. It's suitable for those who have a foundational understanding of SQL and want to apply it in a data analysis context. It's relevant for data scientists and analysts.
While focused on MySQL, this book provides in-depth coverage of database and SQL performance tuning that is applicable to other systems. It's essential for those working with large datasets and high-traffic applications. It's a comprehensive guide for optimizing SQL queries and database infrastructure.
Challenges traditional, rules-based approaches to compliance and advocates for a more integrated, ethics-driven model. It's valuable for deepening understanding by exploring the 'why' behind compliance failures and offering practical strategies for building a more effective compliance culture within organizations. It is relevant for both students and professionals seeking to improve compliance programs.
Provides a broader perspective on data integration by placing it within the larger context of business intelligence. It covers the entire BI lifecycle, from data integration to analytics, and discusses the strategic aspects of leveraging data. It useful resource for understanding how data integration supports business objectives and can be valuable for both technical and business-oriented audiences.
Demonstrates how to unify batch and streaming data on Azure using Delta Lake, Apache Spark, and Azure Synapse Analytics, contrasting storage formats, ingestion patterns, and query federation tradeoffs across cloud engines.
Tailored for aspiring data scientists, this book focuses on the SQL skills needed for data analysis, including dataset construction and manipulation. It bridges the gap between basic SQL and its application in data science workflows. Relevant for those entering or working in the data science field.
While focused on T-SQL (for Microsoft SQL Server), this book provides a deep and rigorous understanding of SQL fundamentals that are applicable to many dialects. It's highly regarded for its clear explanations and challenging examples, making it excellent for solidifying core concepts. It's often used by professionals working with SQL Server.
Explains the core distributed systems mechanics behind massively parallel processing (MPP) cloud data warehouses—shared-nothing hash partitioning, columnar compression, shuffle joins, and transaction isolation.
Bridges the gap between statistical theory and its practical application in data science using R and Python. It focuses on the statistical concepts most relevant to data scientists and provides code examples. It's a useful reference and learning resource for those applying statistics in their work.
For those focusing on cloud-based data integration using Microsoft Azure, this cookbook provides practical recipes for building ETL and ELT pipelines with Azure Data Factory. It covers various aspects of ADF, including connecting to data sources, transforming data, and orchestrating pipelines. valuable resource for practitioners working with Azure's data integration services.
Provides an overview of major IT security standards and frameworks relevant to cybersecurity compliance, such as ISO 27001, NIST, and PCI-DSS. It helps solidify understanding of the technical controls necessary for a robust compliance program in the cybersecurity domain. This is an important reference for IT security practitioners and compliance professionals in technology-focused roles.
Provides a comprehensive international perspective on data privacy laws, covering various jurisdictions beyond just the GDPR. It is valuable for understanding the global landscape of data protection compliance and the challenges of navigating different legal frameworks. This key reference for professionals dealing with international data transfers and privacy compliance.
This guide provides a quick introduction to Power BI for beginners, covering essential topics like data modeling, visualization, and storytelling with data. It's a good resource for getting up to speed quickly with the core functionalities of Power BI.
Equips Synapse architects with a holistic framework for evaluating cloud data warehouse vs. lakehouse tradeoffs, orchestration observability, FinOps compute sizing, and declarative pipeline design.

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