DP-900 Microsoft Azure Data Fundamentals - Exam Prep

 

As promised in my last post after passing the DP-900 Azure Data Fundamentals exam here's my exam preparation guide which provide links to the various resources I used in studying for the different topics.

DESCRIBE CORE DATA CONCEPTS (15-20%)

Describe types of core data workloads

Describe batch data:

https://www.talend.com/resources/batch-processing/

https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/batch-processing

Describe streaming data:

https://hazelcast.com/glossary/stream-processing/

Describe the difference between batch and streaming data:

https://docs.microsoft.com/en-us/learn/modules/explore-core-data-concepts/4-describe-difference

Describe the characteristics of relational data:

https://docs.microsoft.com/en-us/learn/modules/explore-core-data-concepts/3-identify-types-storage

Describe data analytics core concepts

Describe data visualization (e.g., visualization, reporting, business intelligence (BI)):

https://powerbi.microsoft.com/en-us/data-visualization/

Describe basic chart types such as bar charts and pie charts:

https://www.klipfolio.com/resources/articles/what-is-data-visualization

Describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive):

https://docs.microsoft.com/en-us/learn/modules/data-analytics-microsoft/2-data-analysis

https://www.weirdgeek.com/2018/11/types-of-analytics/

Describe ELT and ETL processing:

https://www.talend.com/resources/elt-vs-etl/

Describe the concepts of data processing;

https://www.mbaknol.com/management-information-systems/concept-of-data-processing/

DESCRIBE HOW TO WORK WITH RELATION DATA ON AZURE (25-30%)

Describe relational data workloads

Identify the right data offering for a relational workload:

https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

Describe relational data structures (e.g., tables, index, views):

https://web.csulb.edu/colleges/coe/cecs/dbdesign/dbdesign.php?page=sql/views.php

Describe relational Azure data services

Describe and compare PaaS, IaaS, and SaaS delivery models:

https://www.bmc.com/blogs/saas-vs-paas-vs-iaas-whats-the-difference-and-how-to-choose/

https://docs.microsoft.com/en-us/learn/modules/principles-cloud-computing/5-types-of-cloud-services

Describe Azure SQL Database:

https://azure.microsoft.com/en-gb/services/sql-database/

Describe Azure Synapse Analytics:

https://azure.microsoft.com/en-gb/services/synapse-analytics/

https://docs.microsoft.com/en-us/learn/modules/examine-components-of-modern-data-warehouse/3-explore-azure-data-services-warehousing

Describe SQL Server on Azure Virtual Machine

https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/sql-server-on-azure-vm-iaas-what-is-overview

Describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL:

https://docs.microsoft.com/en-us/learn/modules/explore-relational-data-offerings/6-postgresql-mariadb-mysql

Describe Azure SQL Managed Instance:

https://docs.microsoft.com/en-us/azure/azure-sql/managed-instance/sql-managed-instance-paas-overview

Identify basic management tasks for relational data

Describe provisioning and deployment of relational data services:

https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-relational-database-offerings-azure/4-describe-provision-postgresql-mysql

Describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI):

https://docs.microsoft.com/en-us/learn/modules/deploy-azure-sql-database/3-deploy-single

Identify data security components (e.g., firewall, authentication):

https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-relational-database-offerings-azure/5-configure-relational-data-services

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-errors-issues

https://medium.com/@vmehmeri/troubleshooting-connectivity-in-microsoft-azure-2035c7a43d3f

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?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/ssms/scripting/sqlcmd-use-the-utility?view=sql-server-ver15

https://code.visualstudio.com/

Describe query techniques for data using SQL language

Compare DDL versus DML:

https://docs.microsoft.com/en-us/learn/modules/query-relational-data/2-introduction-to-sql

https://stackoverflow.com/questions/2578194/what-are-ddl-and-dml

Query relational data in PostgreSQL, MySQL, and Azure SQL Database:

https://docs.microsoft.com/en-us/learn/modules/explore-relational-data-offerings/6-postgresql-mariadb-mysql

https://azure.microsoft.com/en-gb/blog/fast-and-easy-dev-with-azure-db-for-mysql-and-azuredb-for-postgresql/?WT.mc_id=DOP-MVP-5003451

DESCRIBE HOW TO WORK WITH NON-RELATIONAL DATA ON AZURE (25-30%)

Describe non-relational data workloads

Describe the characteristics of non-relational data:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data?WT.mc_id=DOP-MVP-5003451

Describe the types of non-relational and NoSQL data:

https://azure.microsoft.com/en-gb/overview/nosql-database/

Recommend the correct data store:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage

Determine when to use non-relational data:

https://azure.microsoft.com/en-gb/overview/nosql-database/

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage (capability matrices)

Describe non-relational data offerings on Azure

Identify Azure data services for non-relational workloads:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-offerings-azure/

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage

Describe Azure Cosmos DB APIs:

https://docs.microsoft.com/en-us/learn/modules/choose-api-for-cosmos-db/

https://nordcloud.com/azure-cosmos-db/

Describe Azure Table storage:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-offerings-azure/2-explore-azure-table-storage

Describe Azure Blob storage:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-offerings-azure/3-explore-azure-blob-storage

Describe Azure File storage:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-offerings-azure/4-explore-azure-file-storage

Identify basic management tasks for non-relational data

Describe provisioning and deployment of non-relational data services:

https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-non-relational-data-services-azure/

Describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI):

https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-non-relational-data-services-azure/

Identify data security components (e.g., firewall, authentication, encryption):

https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-non-relational-data-services-azure/5-describe-configure-non-relational-data-services

https://cloudacademy.com/course/configuring-azure-application-and-data-security/configuring-cosmos-db-security/

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/learn/modules/explore-provision-deploy-non-relational-data-services-azure/5-describe-configure-non-relational-data-services

Identify management tools for non-relational data:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-stores-azure/

DESCRIBE AN ANALYTICS WORKLOAD ON AZURE (25-30%)

Describe analytics workloads

Describe transactional workloads:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction-processing

Describe the difference between a transactional and an analytics workload:

https://www.guru99.com/oltp-vs-olap.html

Describe the difference between batch and real time:

https://www.datasciencecentral.com/profiles/blogs/batch-vs-real-time-data-processing

Describe data warehousing workloads:

https://docs.microsoft.com/en-us/learn/modules/explore-data-ingestion-azure/

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-workload-classification

Determine when a data warehouse solution is needed:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/data-warehousing#:~:text=These%20steps%20help%20guide%20users,transaction%20systems%20for%20performance%20reasons.

Describe the components of a modern data warehouse

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/learn/modules/examine-components-of-modern-data-warehouse/3-explore-azure-data-services-warehousing

https://azure.microsoft.com/en-gb/solutions/data-lake/

https://azure.microsoft.com/en-gb/services/databricks/

Describe modern data warehousing architecture and workload:

https://www.jamesserra.com/archive/2014/12/the-modern-data-warehouse/#:~:text=A%20modern%20data%20warehouse%20consists,%2C%20MapReduce%20tools%2C%20and%20HDFS.

https://docs.microsoft.com/en-us/learn/modules/examine-components-of-modern-data-warehouse/

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-workload-importance

Describe data ingestion and processing on Azure

Describe common practices for data loading:

https://docs.microsoft.com/en-us/learn/modules/explore-data-ingestion-azure/2-describe-common-practices-for-data-loading

https://www.xplenty.com/blog/etl-vs-elt/#:~:text=ETL%20stands%20for%20Extract%2C%20Transform,the%20need%20for%20data%20staging.

Describe the components of Azure Data Factory (e.g., pipeline, activities, etc.):

https://www.cathrinewilhelmsen.net/2019/12/03/overview-azure-data-factory-components/

https://docs.microsoft.com/en-us/learn/paths/data-integration-scale-azure-data-factory/?WT.mc_id=DP-MVP-5001430

Describe data processing options (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory):

https://docs.microsoft.com/en-us/learn/modules/examine-components-of-modern-data-warehouse/3-explore-azure-data-services-warehousing

Describe data visualization in Microsoft Power BI

Describe the role of paginated reporting:

https://docs.microsoft.com/en-us/power-bi/paginated-reports/paginated-reports-report-builder-power-bi

Describe the role of interactive reports:

https://powerbi.microsoft.com/en-us/desktop/

Describe the role of dashboards:

https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboards#:~:text=A%20Power%20BI%20dashboard%20is,tells%20a%20story%20through%20visualizations.&text=Dashboards%20are%20a%20feature%20of,available%20in%20Power%20BI%20Desktop.

Describe the workflow in Power BI:

https://docs.microsoft.com/en-us/learn/modules/get-started-with-power-bi/3-building-blocks-of-power-bi

DATA:Scotland 2019. Unleashing the Guillotine!!!

Friday 13th of September will be my first ever appearance at a conference as a speaker at DATA:Scotland. Needless to say I cannot wait and I'd like to thank the organisers, selectors or whoever it was that drew out the short straw that is me.

I'll be presenting my intriguingly titled 'Guillotines, Sat-Nav and the Query Optimiser' session which I presented at the Manchester and Leeds User Groups earlier this year. The user groups have proved to be a really useful experience as some of the questions that were raised from the audience I've taken onboard and added in, basically I've been stealing their ideas.

My session starts at 12 which unfortunately for me is when my daily caffeine intake usually starts to wear off right at the same time I start to get hungry so I might take up a flask of espresso and a couple of wagon wheels to keep me going. I'll be in conference room 7 which also happens to my lucky number, so that's good news.

Something very new to me is that there will be presenters presenting their sessions at the same time as me and as such I need view these SQL superstars as, well, the competition I guess. I'm not entirely sure what tactics to deploy to get people to come and see me instead; media smear campaigns, good old fashioned kidnapping or perhaps just go really heavy on the propaganda...a bit like this blog post.

The truth is I'm very much overwhelmed at seeing my name up there on that schedule surrounded by people who in all honesty I hold in the absolute highest regard, and I also promise not to kidnap anyone (is their an emoji for fingers crossed behind your back?).

So what can people expect? Well at the moment we're in the midst of an amazing shift in the technical landscape. We've got all this funky cool new stuff like AI, the cloud, containers, Kubernetes etc etc etc and obviously I thought not to cover any of that. No, apparently vintage is all the rage these days so I'm jumping right on that bandwagon!

It may be old school but the query optimiser to me is like the magic box of SQL Server. We all throw queries at it and it goes off and does what it does, that's the beauty of it but at the same time we don't often get chance to open the box and have a good root around - and that's where this session comes in. So I'll be covering how the optimiser works, some of the magic tricks that it performs, how we can use SQL to keep a very close eye on what the optimiser is doing and of course how to break it!

It's worth adding that I will also be trying my best to seamlessly link the query optimiser to guillotines and satellite navigation - that'll teach me to come up with a great title before the actual presentation. I say that but I am currently working on a new session called "fixing your availability groups with sticky back plastic", take note Blue Peter (is that even still on?).

As well as the actual learning stuff (which I promise, there's plenty) there's a few ice breakers in there which I'll not give away right now and there's a good sense of humour throughout, which is mostly directed at the expense of myself.

So if you are attending DATA:Scotland all that's left is for me to beg, plead, perhaps even bribe you to come along to my session; if you choose otherwise I'll not hold it against you...and if you're not attending but stumbled on to this post by accident then thanks for reading if you got this far!