Azure Data Fundamentals (DP-900) - My Story and Study Resources
Reviewed April 2021
Executive technology leader responsible for platform reliability, cloud operations, security posture, and enterprise technology risk within an investor-backed fintech environment. I lead technology operations at the intersection of engineering execution, governance, and business outcomes — ensuring platforms are scalable, resilient, and trusted by investors, regulators, and clients.
Currently VP of DevOps at InvestorFlow, where I focus on building board-ready technology operations, strengthening risk and resilience, and shaping long-term platform strategy to support growth and regulatory confidence.
I passed the Microsoft Azure Data Fundamentals exam at the beginning of April 2021. To give back to the community, I decided to share my experience and the study resources I used to prepare for the exam.
First, why did I take the exam 🤷♂️
I took the DP-900 exam while preparing for the Azure Solutions Architecture exams. Working through the Microsoft Learn modules for AZ-303/304, I found myself reading about database topics. My knowledge on databases is limited (the biggest database I deployed was the time of Access 2007) so I decided to stop preparing for these exams and review data topics.
Microsoft Virtual Training Days 👩🏫
After reviewing the role based certification poster by Microsoft, I identified there was a fundamentals exam. I knew from advertisements and posts within the community that Microsoft offers Virtual Training Days to help individuals getting started with the basics. I visited the Virtual Training Days site and found dates I could attend the video course. After completing the training days, I received a free exam voucher for the DP-900 exam.
Microsoft Learn 🏙️
Even though the video content from the Virtual Training Day was beneficial and covered the topics I expected, I decided to further my knowledge by completing the Azure Data Fundamentals MS Learn modules. I have listed each one below.
Azure Data Fundamentals: Explore non-relational data in Azure
Azure Data Fundamentals: Explore modern data warehouse analytics in Azure
Tip: complete any labs they have to offer during these modules. I find doing practicals actually sink in better than just reading.
Was the above enough ⚖️
Personally no, there was language and services described that I personally want to understand more about before going into the exam. I decided to visit the DP-900 certification page and review the exam skill outline document. I created a spreadsheet of each skill measured and used this to look up any information I can find from the Microsoft website. I have provided below a written out copy of the exam skills outline document with links I found and used to help broaden my knowledge (all from Microsoft sources).
1️⃣ Describe core data concepts (15-20%)
1.1. Describe types of core data workloads
1.1.1. describe batch data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
1.1.2. describe streaming data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
1.1.3. describe the difference between batch and streaming data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/real-time-processing
1.1.4. describe the characteristics of relational data
- https://docs.microsoft.com/en-us/dotnet/architecture/cloud-native/relational-vs-nosql-data
1.2. Describe data analytics core concepts
1.2.1. describe data visualization (e.g., visualization, reporting, business intelligence (BI))
- https://powerbi.microsoft.com/en-us/data-visualization/
1.2.2. describe basic chart types such as bar charts and pie charts
- https://docs.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-types-for-reports-and-q-and-a
1.2.3. describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive)
- https://azure.microsoft.com/en-gb/blog/answering-whats-happening-whys-happening-and-what-will-happen-with-iot-analytics/
1.2.4. describe ELT and ETL processing
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl
1.2.5. describe the concepts of data processing
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-analytical-processing
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction-processing
2️⃣ Describe how to work with relational data on Azure (25-30%)
2.1. Describe relational data workloads
2.1.1. identify the right data offering for a relational workload
- https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview#relational-database-management-systems
2.1.2. describe relational data structures (e.g., tables, index, views)
- https://docs.microsoft.com/en-us/sql/relational-databases/views/views?view=sql-server-ver15
- https://docs.microsoft.com/en-us/sql/relational-databases/tables/tables?view=sql-server-ver15
- https://docs.microsoft.com/en-us/sql/relational-databases/indexes/indexes?view=sql-server-ver15
2.2. Describe relational Azure data services
2.2.1. describe and compare PaaS, IaaS, and SaaS solutions
- https://azure.microsoft.com/en-gb/overview/what-is-paas/
- https://azure.microsoft.com/en-gb/overview/what-is-iaas/
- https://azure.microsoft.com/en-gb/overview/what-is-saas/
2.2.2. describe Azure SQL database services including Azure SQL Database, Azure SQL
- https://docs.microsoft.com/en-us/azure/azure-sql/azure-sql-iaas-vs-paas-what-is-overview
- https://docs.microsoft.com/en-us/azure/azure-sql/database/sql-database-paas-overview
2.3. Managed Instance, and SQL Server on Azure Virtual Machine
2.3.1. describe Azure Synapse Analytics
- https://docs.microsoft.com/en-us/azure/synapse-analytics/overview-what-is
2.3.2. describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL
- https://docs.microsoft.com/en-us/azure/mysql/overview
- https://docs.microsoft.com/en-us/azure/postgresql/overview
- https://docs.microsoft.com/en-us/azure/mariadb/overview
2.4. Identify basic management tasks for relational data
2.4.1. describe provisioning and deployment of relational data services
- Recommend referring to the MS Learn modules
2.4.2. describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
- Recommend referring to the MS Learn modules
2.4.3. identify data security components (e.g., firewall, authentication)
- https://docs.microsoft.com/en-us/azure/azure-sql/database/secure-database-tutorial
2.4.4. identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)
- https://docs.microsoft.com/en-us/azure/azure-sql/database/troubleshoot-common-connectivity-issues
2.4.5. identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.)
- https://docs.microsoft.com/en-us/sql/azure-data-studio/what-is-azure-data-studio?view=sql-server-ver15
- https://docs.microsoft.com/en-us/sql/ssms/sql-server-management-studio-ssms?view=sql-server-ver15
- https://docs.microsoft.com/en-us/sql/tools/sqlcmd-utility?view=sql-server-ver15
2.5. Describe query techniques for data using SQL language
2.5.1. compare Data Definition Language (DDL) versus Data Manipulation Language (DML)
- https://docs.microsoft.com/en-us/sql/t-sql/statements/statements?view=sql-server-ver15
2.5.2. query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL
- https://docs.microsoft.com/en-us/azure/azure-sql/database/connect-query-portal
- https://docs.microsoft.com/en-us/azure/postgresql/how-to-connect-query-guide
- https://docs.microsoft.com/en-us/azure/mysql/how-to-connect-overview-single-server
3️⃣ Describe how to work with non-relational data on Azure (25-30%)
3.1. Describe non-relational data workloads
3.1.1. describe the characteristics of non-relational data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
3.1.2. describe the types of non-relational and NoSQL data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
3.1.3. recommend the correct data store
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
3.1.4. determine when to use non-relational data
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
3.2. Describe non-relational data offerings on Azure
3.2.1. identify Azure data services for non-relational workloads
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
3.2.2. describe Azure Cosmos DB APIs
- https://docs.microsoft.com/en-us/rest/api/cosmos-db/
3.2.3. describe Azure Table storage
- https://docs.microsoft.com/en-us/azure/storage/tables/table-storage-overview
3.2.4. describe Azure Blob storage
- https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-overview
3.2.5. describe Azure File storage
- https://docs.microsoft.com/en-us/azure/storage/files/storage-files-introduction
3.3. Identify basic management tasks for non-relational data
3.3.1. describe provisioning and deployment of non-relational data services
- Recommend referring to the MS Learn modules
3.3.2. describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
- Recommend referring to the MS Learn modules
3.3.3. identify data security components (e.g., firewall, authentication, encryption)
- https://docs.microsoft.com/en-us/azure/azure-sql/database/secure-database-tutorial
3.3.4. identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)
- https://docs.microsoft.com/en-us/azure/azure-sql/database/troubleshoot-common-connectivity-issues
3.3.5. identify management tools for non-relational data
4️⃣ Describe an analytics workload on Azure (25-30%)
4.1. Describe analytics workloads
4.1.1. describe transactional workloads
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction-processing
4.1.2. describe the difference between a transactional and an analytics workload
- https://docs.microsoft.com/en-us/azure/cosmos-db/analytical-store-introduction
4.1.3. describe the difference between batch and real time
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/real-time-ingestion
4.1.4. describe data warehousing workloads
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/data-warehousing
4.1.5. determine when a data warehouse solution is needed
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/data-warehousing
4.2. Describe the components of a modern data warehouse
4.2.1. describe Azure data services for modern data warehousing such as Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight
- https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction
- https://docs.microsoft.com/en-us/azure/synapse-analytics/overview-what-is
- https://docs.microsoft.com/en-us/azure/databricks/scenarios/what-is-azure-databricks
- https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-overview
4.2.2. describe modern data warehousing architecture and workload
- https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/data-warehousing
4.3. Describe data ingestion and processing on Azure
4.3.1. describe common practices for data loading
- https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/data-loading-best-practices
4.3.2. describe the components of Azure Data Factory (e.g., pipeline, activities, etc.)
- https://docs.microsoft.com/en-us/azure/data-factory/introduction
4.3.3. describe data processing options (e.g., Azure HDInsight , Azure Databricks, Azure Synapse Analytics, Azure Data Factory)
- https://docs.microsoft.com/en-us/analysis-services/multidimensional-models/processing-options-and-settings-analysis-services?view=asallproducts-allversions
4.4. Describe data visualization in Microsoft Power BI
4.4.1. describe the role of paginated reporting
- https://docs.microsoft.com/en-us/power-bi/paginated-reports/paginated-reports-faq
4.4.2. describe the role of interactive reports
- https://docs.microsoft.com/en-us/power-bi/create-reports/service-reports-visual-interactions
4.4.3. describe the role of dashboards
- https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboards
4.4.4. describe the workflow in Power BI
- No content found
Any other resources before I took the exam 📺
My exam was booked for the afternoon so I decided to get some type of morning cram in by watching some video content that would refresh the new information I learnt. The top hit I found on YouTube was from John Savill who provides a one hour and twenty minute whiteboard video covering the information I learnt from all of the above. This really helped so I would recommend watching it (remember to support content creators by liking and subscribing to their channels):
DP-900 Azure Data Fundamentals Exam Cram Whiteboard Video
Other than this, I didn't use any other resource to prepare for the exam.
Conclusion ✍️
This post wasn't to provide tips and tricks to the exam. The idea of this post is to tell you what got me onto the exam, what resources I found on the way and to give back to the community where I have farmed resources for many years. The intention wasn't to get another certification but to skill up in an area where I was lacking information for another certification I was trying to attain. In the end, it was a bonus for me to be able to sit the exam for free and pass.
