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DP-900: Azure Data Fundamentals Exam Preparation

Name: DP-900: Azure Data Fundamentals Exam Preparation
Rating: 4.2 (59 reviews)

DP-900-Master the fundamentals of Microsoft Azure data services & pass the DP-900 exam with confidence

Created byStep2C Education

Last updated 10/2025

English

What you'll learn

You will understand core data concepts.
You will learn how data is stored and processed in Azure.
You will understand relational data workloads.
You will understand non-relational data workloads.
You will understand modern data warehouse analytics.
You will learn different Azure data services.
You will understand security and compliance in azure cloud.

Course content

7 sections • 32 lectures • 2h 31m total length

Descriptive Data Analysis2:24
Explore descriptive data analysis, the simplest technique that uses historical data to reveal what happened in the past, such as revenue and sales trends.
Diagnostic Data Analysis1:38
Identify why events happen using diagnostic data analysis, not only what happened in descriptive analysis. Explore examples like cart abandonment and payment bugs to explain sales trends.
Prescriptive Analysis1:37
learn prescriptive data analysis to generate recommendations and concrete actions that improve sales, such as re-engaging customers after an offer with targeted incentives.
Predictive Analysis1:12
Forecast future outcomes by analyzing historical data and current status, and applying machine learning and artificial intelligence techniques to predict what will happen.
Cognitive analysis1:38
Explore cognitive data analysis, a machine learning approach that models how humans think to understand data and imitate predictions. See examples such as creating closed captions and transcribing audio.

Core Data Concepts4:38
Identify how database management systems store data in relational tables and organize it into tables, columns, and rows. Explore SQL basics for select and insert statements and schema usage.
Use Of View2:08
Create views to turn complex select statements into virtual tables, saving the query as a reusable result. Use the view to hide complexity and simplify data access.
Use And Type Of Index4:33
Explore how indexes speed data retrieval in a database, including clustered indexes for sorted data in physical order and non-clustered indexes for fast lookups on where conditions.
Use Of Stored Procedure1:54
Learn how a stored procedure stores a block of code in a database management system, via create procedure, enabling reuse by name and execution with begin and end around statements.
DDL Vs DML5:43
Explore the differences between ddl, dml, dcl, and tcl, and see how sql statements create, modify, and manage database structures and data.
TCL2:14
Explore TCL transaction control language and how begin, commit, rollback, savepoint, and set transaction ensure atomic, all-or-nothing execution for grouped SQL statements like money transfers.
DQL1:46
Explore data query language with the select statement to retrieve data from tables using where, order by, group by, and having for filtering and aggregation, noting select cannot update data.
SQL: List Of Aggregate Functions2:11
Explore aggregate functions in a database, using count, sum, average, min, max, and distinct with count, and group by to summarize sales by product in a product table.
Concepts Of Joins & Keys5:23
Learn how to combine data from multiple tables using joins, including inner, left, right, outer, cross, and self joins, and understand primary and foreign keys to enforce relationships.
Other Core Data Concepts And Important Exam Questions And Answers23:22
Explore relational tables, rows, and columns, and how views, permissions, and data types support consistent data. Compare OLTP and OLAP, and review Azure data options and tools.
Normalizations Concepts And Key Points5:52
Learn how normalization divides large tables into smaller ones to improve data consistency and reduce duplication, with city and state examples and a contrast to denormalized OLTP and OLAP designs.

Different Types Of Data Analysis5:06
Explore descriptive, diagnostic, prescriptive, predictive, and cognitive analytics, and learn how each type explains past events, why they happened, guides actions, forecasts outcomes, and detects patterns.
Star Schema and Snowflake Schema2:31
Explore star and snowflake schemas in data warehouses by identifying fact tables and surrounding dimension tables, with snowflake schemas showing dimension-to-sub-dimension links.
Azure Synapse Analytics1:57
Azure Synapse Analytics combines data warehouse concepts with big data processing using Azure data services, distributing data across computing nodes for massively parallel processing and scalable analytics.
Demo: Create Azure Synapse Workspace5:51
Create an Azure Synapse Analytics workspace by selecting a resource group, a unique workspace name, East US location, Gen2 data lake storage, and a file system, then configure security options.
Demo: Synapse Workspace4:17
Explore how to access an Azure Synapse workspace, manage pools (serverless SQL, SQL pools, Apache Spark pools, Data Explorer pool), monitor usage, and configure data lake storage access controls.

Batch Processing Vs Stream Processing5:48
Compare batch processing and stream processing by data collection timing and latency. Batch processes data in bulk with delay, while stream processes data in real time as it is generated.
Azure Storage Account And Azure Data Lake G215:40
Explore cloud service models (IaaS, PaaS, SaaS) and storage redundancy for Azure Data Lake Gen2, plus ACL and RBAC, and SQL options: database, managed instance, and SQL Server on VM.

Describe three different ways to represent data10:26
Describe three data representations—structured, semi-structured, and unstructured—and illustrate with Excel and relational databases, JSON format, and media/text data, highlighting schema evolution and storage implications.
Identify different options for data storage in Azure5:28
Identify Azure storage options for structured, semi-structured, and unstructured data, including relational databases and Cosmos DB APIs, plus blob storage.
Use Of Different File Format5:58
Identify file formats for structured, semi-structured, and unstructured data, including CSV, Excel, JSON, XML, Avro, and Parquet. Understand Parquet’s columnar storage for big data and Avro’s streaming and schema evolution.
Describe different types of data workloads4:25
Explore types of data workloads, from OLTP transaction systems to data warehouses, and how ETL/ELT, data integration, and analytics tools power dashboards and machine learning workloads.
OLTP Workload4:54
Analyze OLTP workloads as source systems that capture real-time, structured transactions with fast inserts, updates, and deletes using normalized, multi-table databases in Azure SQL DB, Cosmos DB, PostgreSQL, and MySQL.
Data Warehouse Workload3:43
Centralize data from OLTP and external systems into a data warehouse for historical analysis. Clean and transform data to support read-optimized reports and dashboards using star or snowflake schemas.
ETL -ELT Workload2:16
Explore ETL and ELT data integration workflows that read from OLTP sources, transform data, and load it into a data warehouse using Azure Data Factory, Synapse Pipeline, and Databricks.
Other Workload2:50
Explore OLAP and BI in Azure data workloads, reading from data warehouses with denormalized schemas using Power BI, Azure Analysis Service, and Synapse.

Requirements

Internet Connections
Azure cloud account(optional to follow our labs)

Description

DP-900 Exam Practice Test

Welcome to the DP-900 Exam preparations course! This course provides you with a comprehensive set of practice questions designed to simulate the format and difficulty level of the actual DP-900 exam. Our goal is to help you prepare effectively and build your confidence.

Important Information:

Simulation of Real Exam: The practice questions included in this course are similar to those you can expect on the real DP-900 exam. However, please note that these are not actual exam questions.
Accuracy and Errors: While we have made our best efforts to ensure the accuracy of the practice questions and information provided, we acknowledge that there may be errors or inaccuracies. This practice test is not error-free, and we cannot be held responsible for any issues that may arise as a result of using this material.
Content Volume: The course contains over 100 practice questions. This extensive set of questions is designed to give you a thorough preparation experience.

This course is designed for individuals who want to learn the fundamentals of data storage and processing in Microsoft Azure. The course covers a range of topics, including the different types of data storage options available in Azure, how to manage and secure data in Azure, and how to process data using Azure services.

The course begins by introducing the fundamental concepts of data storage and processing, including data types, data sources, and data models. It then covers the different types of data storage options available in Azure, including Azure Blob Storage, Azure File Storage, and Azure Table Storage. Students will learn how to use these services to store and manage data in the cloud.

This comprehensive DP-900 Exam Preparation Course is designed to help you prepare for the Microsoft Azure Data Fundamentals (DP-900) certification exam. It covers all the exam topics and provides you with the necessary knowledge and skills to pass the exam with confidence.

Course Features:

Complete Coverage of Exam Topics: The course covers all the key topics included in the DP-900 exam, ensuring that you have a solid understanding of Azure data services and concepts.
Video Content: The course includes over 1.45 hours of high-quality video content. The videos are presented by experienced instructors who explain the concepts, demonstrate practical examples, and provide insights to help you grasp the exam objectives effectively.
Exam Tips and Strategies: Throughout the course, you will receive valuable exam tips and strategies to enhance your exam performance. These insights will help you approach the exam with confidence and maximize your chances of success.

Whether you are new to Azure data services or looking to validate your existing knowledge, this DP-900 Exam Preparation Course provides you with the necessary resources to prepare effectively.

Please note that while this course is designed to cover all the exam topics and provide extensive practice materials, success in the exam also depends on individual effort, additional study, and practical experience with Azure data services.

This comprehensive DP-900 Exam Preparation Course is designed to provide in-depth coverage of key Azure data services and concepts, preparing you for the Microsoft Azure Data Fundamentals (DP-900) certification exam. The course focuses on the following topics:

Azure SQL Database: Learn about Azure's fully managed relational database service, including its features, benefits, and how to provision and manage databases in the Azure environment.
Azure Storage Account: Understand the different storage options available in Azure, such as Azure Blob Storage, Azure Files, and Azure Queue Storage. Explore how to create and manage storage accounts and effectively store and retrieve data.
Azure Data Lake Storage Gen2: Gain insights into Azure Data Lake Storage Gen2, which combines the scalability of Azure Blob Storage with the hierarchical file system capabilities of Azure Data Lake Storage. Learn how to store and process large amounts of unstructured and structured data.
Azure Data Factory: Explore Azure Data Factory, a cloud-based data integration service that enables you to create, orchestrate, and manage data pipelines and workflows. Discover how to ingest, transform, and load data from various sources to different destinations.
Relational and Non-Relational Data Stores: Understand the differences between relational and non-relational data models and explore Azure's offerings for both. Learn about Azure Cosmos DB, a globally distributed, multi-model database service, and its support for various data models.
Data Processing: Discover Azure's data processing capabilities, including Azure Databricks and Azure HDInsight. Learn how to leverage these services for big data analytics, batch processing, and real-time streaming analytics.
Data Visualization: Explore Azure's data visualization tools, including Power BI. Learn how to create interactive dashboards and reports, and gain insights from your data through visualizations and analytics.

The course includes over 2.00 hours of video content, covering each topic in detail.

By completing this course, practicing with the provided materials, and applying your knowledge to real-world scenarios, you will be well-prepared to pass the DP-900 exam and obtain your Microsoft Azure Data Fundamentals certification. Please note that while the course covers a broad range of topics, individual effort, additional study, and practical experience will further enhance your exam preparation.

The course also covers how to manage and secure data in Azure. Students will learn about data encryption, access control, and backup and recovery options in Azure. They will also learn how to monitor and troubleshoot data storage and processing issues in Azure.

In addition to data storage, the course covers how to process data using Azure services. Students will learn about Azure Data Factory, Azure Databricks, and Azure Stream Analytics, and how to use these services to transform and analyze data in real-time.

Throughout the course, students will have the opportunity to work with real-world scenarios and use cases to reinforce their learning. By the end of the course, students will have a solid understanding of the fundamental concepts of data storage and processing in Azure, and will be well-equipped to pass the Microsoft DP-900 certification exam.

Disclaimer:

No Responsibility for Errors: We strive to provide the most accurate information possible, but this practice test may contain errors. We are not responsible for any issues or consequences that arise from using this practice material.
Effort to Provide Correct Information: We have put forth our best effort to share correct and relevant information to assist in your exam preparation. However, the material is provided as-is and should be used as a supplementary resource.

Our Best Wishes:

We want to congratulate you on taking this important step towards your DP-900 certification. We believe that with dedication and practice, you can achieve success. Best wishes for your preparation and the exam ahead!

We hope you find this practice test beneficial in your journey to becoming certified. Good luck!

Who this course is for:

Professionals who are new to cloud computing and want to understand the basics of cloud services and Azure.
Developers who want to learn how to create cloud solutions with Azure.
Data professionals who want to learn how to work with Azure data services.
IT professionals who want to gain an understanding of Azure and how it can be used in their organization.
Students who are interested in learning about cloud computing and Azure.
If you are preparing for the DP-900 exam (Microsoft Azure Data Fundamentals) and want to ensure your success, consider enrolling in our course

DP-900: Azure Data Fundamentals Exam Preparation

What you'll learn

Explore related topics

Course content

Different Types Of Data Analysis5 lectures • 8min

Core Data Concepts-Relational Data In Azure11 lectures • 1hr

Data Analytics in Azure: Data Warehouse Concepts5 lectures • 20min

Data Processing Concepts-Explore fundamentals of real-time analytics2 lectures • 21min

Important File Types1 lecture • 2min

Core Data Concepts (25–30%) For DP-900 Exam8 lectures • 40min

Practice Questions And Answer Set -DP 9000

Requirements

Description

Who this course is for: