
Explore how to represent data across formats such as structured tables, NoSQL databases, semi-structured JSON, and unstructured media. Learn how each format stores attributes and supports different use cases.
Identify the key data roles and responsibilities, including database administrators, data engineers, and data analysts, and learn how they set up, maintain, clean, transform, store, and derive value from data.
Explore setting up an Azure storage account and using a free Azure account for hands-on practice, while navigating the Azure portal to prepare for Azure services.
Learn how to create an Azure free account by setting up a Microsoft account, verifying via email and phone, and using the $200 free credit during the first 30 days.
Explore how security defaults add multi-factor prompts during Azure login and how to disable or re-enable them via Microsoft Entra ID properties, with a note on trade-offs.
Explore infrastructure as a service via virtual machines and platform as a service with Azure SQL Database for hosting relational databases on Azure, including pay-as-you-use pricing.
This chapter focuses on creating a virtual machine
connect to a deployed sql virtual machine in azure using native rdp, download the rdp file, and log in with sqladmin credentials via its public ip address.
This chapter focuses on installing Microsoft SQL Server
This chapter focuses on connecting to Microsoft SQL Server
This chapter focuses on creating an Azure SQL database
Install Azure Data Studio on your laptop, covering Windows system installer (x64) and macOS availability, with download, license acceptance, next, and install steps. Launch the app to explore the interface.
Install Azure Data Studio on macOS, connect to a Microsoft SQL Server, and explore databases and tables, including the App DB.
Explore core database terms like database, relational database, table, columns and rows, SQL, and result set to understand how data is stored, organized, and retrieved.
This chapter focuses on different types of SQL statements
Sort query results using the order by clause, ordering by unit price in ascending or descending order. Combine order by with where clauses to create multi-clause queries in SQL.
Learn how to use the SQL inner join to combine data from the SalesOrderDetail and Product tables, using ProductID in the ON clause and table aliases for clarity.
Learn how to create and relate course, student, and orders tables by defining primary keys and foreign keys, enforce relationships, and perform updates, inserts, deletes, and drops.
Create a new sql login in the master database, map it to a user in appdb, and grant select permission on tables to enable data access for the new user.
This chapter focuses on table views
This chapter focuses on resources on table views
This chapter focuses on table indexes
Demonstrates creating a customers table and a clustered index on customer id, showing how the index transforms a full table scan into a fast, index-based lookup.
Learn how transparent data encryption protects data at rest in Azure SQL Database, SQL Managed Instance, and Azure Synapse by encrypting disk-stored files with a key.
Explore the Azure SQL managed instance, a fully managed paas offering with 100 percent SQL Server compatibility and automated backups, deployed in a private virtual network.
Explore the Azure SQL Database serverless compute tier, billed per second and automatically pausing when idle, ideal for variable usage patterns compared to DTU-based purchasing.
Create an Azure storage account by selecting a subscription and resource group, entering a unique name in North Europe, selecting locally-redundant storage, and exploring blob, file shares, queues, and tables.
This chapter focuses on Azure Storage accounts - blob service
This chapter focuses on Azure Storage accounts - Data Redundancy
This chapter focuses on Azure Storage accounts - Service tiers
This chapter focuses on Azure Storage accounts - File service
Learn how to connect to an Azure file share from macOS by using the macOS script, copy it to the clipboard, paste into the terminal, and access files.
This chapter focuses on Azure Storage accounts - Table service
This chapter focuses on Azure Storage Explorer
Explore Azure Storage Explorer on macOS ARM64, sign in with Azure, load subscriptions, and navigate storage accounts, containers, and file shares.
This chapter focuses on Azure Storage Accounts - Firewall
Explore Azure Cosmos DB concepts, including the NoSQL API, databases and containers, logical partitions guided by partition keys, and throughput via request units for fast, scalable queries.
Explore global data replication in Azure Cosmos DB with read and write regions, reducing latency and costs, and understand when to enable multiple region writes.
Create an Azure Cosmos DB account with the Gremlin API, then build a graph of employees and departments by adding vertices and edges, using city as the partition key.
Review non-relational data concepts and flexible schemas. Outline Azure storage services, including blob, file share, table, and queue, storage tiers, and Cosmos DB APIs with geo-redundancy.
Explore Azure Blob Storage and Azure Data Lake Gen2, Azure SQL Database, and Azure Cosmos DB, and learn to extract data, transform, and move to a destination with Azure Synapse.
Explore Azure Synapse Analytics as an enterprise data platform, covering Synapse SQL, Apache Spark, Data Factory features, Data Lake Storage Gen2, and Studio‑driven tooling for ingestion, processing, and reporting.
Explore using the Azure Synapse serverless SQL pool to analyze CSV data in an Azure Data Lake Gen2 storage account via Open Synapse Studio, with costs based on data processed.
Explain how a SQL data warehouse supports analysis with OLAP design, contrasting online transactional processing with historical data storage, and describing fact and dimension tables in star or snowflake schemas.
Explore how fact tables store quantitative sales data and how dimension tables provide context with product and region details for effective SQL data warehouse design and analysis.
Learn to set up a dedicated SQL pool in Azure Synapse, manage data warehousing units and cost, pause compute, and build a fact-based table by joining SalesOrderHeader and SalesOrderDetail.
Set up a dedicated sql pool in azure synapse, create a fact table, and copy data from azure sql into the pool using a data factory pipeline, with monitoring.
Explore how to create and use an Apache Spark pool in Azure Synapse to read data from a Data Lake Gen2 storage account using notebooks and a data frame.
Explore Azure Data Factory, a cloud-based ETL and data integration service that builds pipelines to extract, transform, and load data across sources and destinations.
Create an Azure Data Factory resource, design a pipeline with copy data activity to convert CSV to Parquet, and copy Parquet to a dedicated SQL pool in Azure Synapse.
Use mapping data flows in Azure Data Factory to transform data with spark. Filter null resource groups from CSV in data lake Gen2 and load into SQL pool via pipeline.
Create an Azure stream analytics job with a csv input from Azure Data Lake Gen2 and an Azure Synapse dedicated sql pool output, then verify results after uploading ActivityLog.csv.
Learn to read csv data from an Azure Data Lake Gen2 storage using a Spark-based Databricks notebook, creating a minimal compute cluster, loading into a data frame, and displaying results.
Learn to connect Power BI Desktop to Azure Data Lake Gen2 Storage, fetch activity log data with a SAS token, transform via Power Query, and visualize operation counts by status.
Learn to create a calculated column in Power BI Desktop using the Power Query Editor by multiplying order quantity by unit price to compute an initial total.
Master paginated reports with Power BI Report Builder, publish to the Power BI service, and understand that advanced license is required beyond free Power BI for multi-page tables.
Explore the range of Power BI visualizations, from bar and column charts to maps and scatter charts, and learn how charts like key influencers, KPIs, tables, and treemaps convey data.
Explore Azure HDInsight as a managed cloud analytics service for DP-900 Microsoft Azure data fundamentals, supporting Apache Spark, Apache Hive, Kafka, and Hadoop for enterprise data analysis, with cluster creation.
Deploy an Azure Event Hubs namespace and an Event Hub in North Europe with basic pricing. Configure diagnostic settings to stream web app logs to the Event Hub.
Configure an Azure Stream Analytics input from an Azure Event Hub to process web app http logs, extract method, status, uri, and ip with cross apply and test query.
Schedule your DP-900 exam through Pearson after finishing the course. Practice with the assessment and quizzes to reinforce key Azure data fundamentals concepts.
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Version 4.0 - June 2024
Entire course revamped with all chapters re-recorded. This is to align the course with the updated exam objectives and services on the Azure platform.
Version 3.1 - July 2023
Changed the chapters which relate onto the working of the storage account service. This is to keep in line with the changes made to the service.
For Azure Databricks, changed the way we access data in a storage account. This is to keep in line with the recent recommendations on accessing a storage account from Azure Databricks.
Version 3.0 - Nov 2022
Carried out a major refresh of the course. The major refresh includes updating all of the videos to reflect the newer changes to Azure services. This refresh was also done to align with the newer exam objectives.
Version 2.0 - Feb 2021
Added chapters on
Azure SQL Managed Instance
Azure Cosmos DB - Mongo DB API
Azure Cosmos DB - Gremlin API
Revised chapters on Azure Databricks
Updated chapters on Azure Synapse Analytics to reflect recent changes in Azure on this service
Added a completely NEW SECTION. This section includes
Working with SQL commands on data
Working with data in Power BI
Additional aspects related to Azure Data Factory
This course is designed for students who want to attempt the Exam DP-900: Microsoft Azure Data Fundamentals
This course has contents for the Exam DP-900
The objectives covered in this course are
Describe core data concepts (15-20%)
Describe how to work with relational data on Azure (25-30%)
Describe how to work with non-relational data on Azure (25-30%)
Describe an analytics workload on Azure (25-30%)
The following key aspects are covered in this course
Working with SQL databases - Here we will see how to work with SQL databases using Microsoft SQL Server on an Azure virtual machine.
We will then explore the Azure SQL database service
We will look at non-relational data stores such as Azure Storage accounts and Azure Cosmos DB
We will look at Analytical services such as Azure Synapse
We will see how to use Azure Data Factory as an ETL tool
This course has a number of videos that will help the student be prepared for the DP-900 exam. Right from the basics on understanding the different data services to knowing how they can work together.