Azure Data Fundamentals Certification (DP-900) - Full Course to PASS the Exam

Prepare for the Azure Data Fundamentals Certification and pass!

☁️ Data Concepts
🎤 (0:10:12) Auzre Core Data Related Services
🎤 (0:14:55) Types of Cloud Computing
🎤 (0:16:56) Azure Data Related Roles
🎤 (0:18:42) Database Administrator Common tools
🎤 (0:20:27) Data Engineering Common tools
🎤 (0:21:43) Data Analyst Common tools
🎤 (0:22:26) Data Overview
🎤 (0:23:43) Introduction to Data
🎤 (0:24:32) Data documents
🎤 (0:25:30) Data sets
🎤 (0:28:31) Data types
🎤 (0:32:15) Schema vs Schemaless
🎤 (0:34:09) Query and Querying
🎤 (0:35:54) Batch vs Stream processing
🎤 (0:38:30) Relational data
🎤 (0:40:35) Relational data Relationships
🎤 (0:42:07) Row store vs Column store
🎤 (0:43:44) Database Index
🎤 (0:45:05) Data Integegrity vs Data Corruption
🎤 (0:47:11) Normalized vs Denomralized data
🎤 (0:48:32) Pivot table
🎤 (0:50:10) Strongly consistent vs Eventually consistent
🎤 (0:51:33) Synchronus vs Asynchronous
🎤 (0:53:29) Non relational data
🎤 (0:54:29) Data source
🎤 (0:55:41) Data store
🎤 (0:56:32) Database
🎤 (0:57:56) Data warehouse
🎤 (0:59:39) Data mart
🎤 (1:00:36) Data lakes
🎤 (1:01:42) Data lakehouse
🎤 (1:03:12) Data structures
🎤 (1:04:02) Unstructured data
🎤 (1:04:47) Semi structured
🎤 (1:06:10) Semi structured Data Structures
🎤 (1:07:16) Semi structure JSON
🎤 (1:08:11) semi structure ORC
🎤 (1:09:39) semi structure Parquets
🎤 (1:10:35) semi structure AVRO
🎤 (1:11:25) Structured Data
🎤 (1:11:56) Data mining
🎤 (1:13:02) Data mining methods
🎤 (1:14:28) Data wrangling
🎤 (1:15:31) Ddata modeling
🎤 (1:17:18) ETL vs ELT
🎤 (1:19:18) Data analytics
🎤 (1:20:14) Key performance indicators KPI
🎤 (1:21:23) Data Analytic Techniques
🎤 (1:23:02) Microsoft One Drive
🎤 (1:24:20) Microsoft Sharepoint
🎤 (1:25:49) Data Core Concepts CheatSheet

☁️ Azure Synapse and Data Lake
🎤 (1:33:36) Azure Synapse Analytics
🎤 (1:35:26) Sypanse SQL and pools
🎤 (1:37:19) Synapse Key Features
🎤 (1:38:31) Azure Data Lake Gen 2
🎤 (1:40:03) Polybase
🎤 (1:40:50) Synapse ELT
🎤 (1:41:51) Azure Data Lake Analytics
🎤 (1:43:05) Azure Sypanse and Data Lakes CheatSheet

☁️ Account Storage
🎤 (1:44:25) Azure Blob Storage
🎤 (1:45:20) Azure Files
🎤 (1:47:14) Azure Storage Accounts CheatSheet

☁️ Power BI
🎤 (1:48:07) Business Intelligence
🎤 (1:48:40) Power BI
🎤 (1:51:29) Power BI Visualizations
🎤 (1:53:13) Power BI Embedded
🎤 (1:54:02) Power BI Interactive Reports
🎤 (1:55:36) Power BI Service and Dashboards
🎤 (1:56:47) Reports vs Dashboards
🎤 (1:57:47) Paginated Reports
🎤 (1:58:57) Power BI CheatSheet

☁️ Relational Databases
🎤 (2:00:38) Structured Query Language
🎤 (2:01:48) OLAP vs OLAP
🎤 (2:03:14) Open Source Relational Databases
🎤 (2:06:01) Read Replicas
🎤 (2:07:10) Citus Postgres Hyperscale
🎤 (2:08:03) Azure SQL Family
🎤 (2:10:30) Elastic pools
🎤 (2:11:45) Relational Databases CheatSheet

☁️ T SQL
🎤 (2:14:12) T SQL
🎤 (2:15:40) Data Defintion Language
🎤 (2:16:43) Data Manipulation Language
🎤 (2:18:02) Data Query Language
🎤 (2:19:08) Data Control Language
🎤 (2:19:36) Transaction Control Langauge
🎤 (2:20:22) SQL Document Comparsions
🎤 (2:21:10) T SQL CheatSheet

☁️ Database Security
🎤 (2:22:01) Connectivity Architecture
🎤 (2:23:13) Database Authentication
🎤 (2:24:41) Network Connectivity
🎤 (2:25:19) Azure Defender for SQL
🎤 (2:25:54) Azure Database Server Firewalls
🎤 (2:27:00) Always Encrypted
🎤 (2:27:47) Role Based Access Controls
🎤 (2:28:48) Transparent Data Encryption
🎤 (2:29:49) Dynamic Data Masking
🎤 (2:31:02) Private Links
🎤 (2:31:57) Database Security Cheatsheet

☁️ Azure Tables Cosmos DB
🎤 (2:34:13) Key Value Store
🎤 (2:35:40) Document Store
🎤 (2:36:33) Mongo DB
🎤 (2:38:35) Graph Database
🎤 (2:39:42) Apache Tinkerpop and Gremlin
🎤 (2:41:23) Azure Tables
🎤 (2:42:45) Azure Cosmos DB
🎤 (2:44:40) Azure Table Account Storage vs Cosmos DB
🎤 (2:46:39) Azure Tables and CosmosDB CheatSheet

☁️ Hadoop Systems
🎤 (2:48:29) Apache Hadoop
🎤 (2:49:57) Apache Kafka
🎤 (2:50:53) HDInsights
🎤 (2:52:05) Hadoop CheatSheet

☁️ Azure and Databricks
🎤 (2:53:21) Apache Spark
🎤 (2:55:04) Azure Databricks
🎤 (2:57:16) Apache Spark and Databricks CheatSheet

☁️ ELT and SQL Tools
🎤 (2:58:46) SQL Server Management Studio
🎤 (2:59:37) SQL Server Data Tools
🎤 (3:00:58) Azure Data Studio
🎤 (3:01:48) Azure Data Factory
🎤 (3:02:59) SQL Server Integration Services
🎤 (3:04:08) ETL and SQL Tools CheatSheet

☁️ Follow Alongs
🎤 (3:05:38) Install and Use Power BI
🎤 (3:08:17) Launch Azure SQL and Use Data Studio
🎤 (3:34:53) Use Azure SQL as data source in Power BI
🎤 (3:44:20) Use SSMS to perform a query on Azure SQL
🎤 (3:47:37) Create Blob and File storage
🎤 (3:57:36) Explore CosmosDB various NoSQL engines
🎤 (4:27:08) Create a ELT job from Azure SQL to Blob Storage
🎤 (4:33:06) Explore Azure Databricks
🎤 (4:39:49) Explore Azure Synapse Analytics
🎤 (4:44:47) Cleanup

[k]

CheatSheets:
Data Core Concepts: 1:25:44
Azure Sypanse and Data Lakes: 1:43:02
Azure Storage Accounts: 1:47:09
Power BI: 1:58:54
Relational Databases: 2:11:42
T-SQL: 2:21:06
Database Security: 2:31:54
Azure Tables and CosmosDb: 2:46:36
Hadoop: 2:52:02
Apache Spark and Databricks: 2:57:13
ETL and SQL Tools: 3:04:05

[carbon-kevin]

For anyone taking this test, I would encourage that you study Azure Data API's very well. I took the test today and was not prepared for the number of questions regarding that topic. Still passed, but wish I would have been a bit more prepared.

[ahmedmohiuddin]

Thank you so much for your great works. You did a fantastic job. You covered almost everything in a nutshell for the Azure world. You are helping us way way more than we are helping you. Thanks again

[CarlaJenkinsTV]

Thank you for another brillant Azure certification tutorial Andrew! Your DP-900 will help so many people!

[carlosortegamorales]

Andrew, i watched your video a couple of times and passed the exam! Thanks for putting this together. There you go..!

[pranaymandadapu]

Damn, this guy! I passed the exam with an 866 score, I am in absolute aww I prepared for 4-5 hours I am done. Thank you once again for the free content.

[kavasr]

This is waaaay more than what you actually need to learn for the test. You need half of these or less but it's still a very good and comprehensive content if you're interested in these concepts.

[Purplepimple]

Thanks for your expertise and effort of putting this together. I really enjoyed your content! Still a lot to learn. Looking forward for your other DP related trainings :)

[nerdindian]

1:00:34 - Data lake
1:01:42 - Data lakehouse
1:03:09 - Data Structures
1:04:01 - Unstructured Data
1:04:45 - Semi Structured Data
1:11:21 - Structured Data
1:11:53 - Data Mining
1:12:57 - Data Mining methods
1:14:24 - Data Wrangling

[kcnfhdn]

🎯 Key Takeaways for quick navigation:

01:37 🌐 *Introduction to DP-900 Certification*
03:27 📚 *Pathways to DP-900 Certification*
04:55 💡 *Preparing for DP-900 Exam*
06:05 📘 *Exam Guide Overview*
09:56 📊 *Detailed Exam Topics*
13:27 📦 *Azure Data Services Overview*
15:47 ⚙️ *Cloud Computing Models for Data Services*
17:09 👥 *Azure Data Roles Overview*
18:48 🧰 *Common Tools for Database Administrator*
20:27 🛠️ *Azure Data Services Overview*
*- Azure Data Studio (for Mac or Linux)*
*- SQL Server Management Studio (SSMS, for Windows)*
*- Azure Portal and CLI for database configuration*
*- Azure Resource Manager templates for infrastructure as code.*
21:39 🧰 *Data Engineering Tools*
*- Various SQL languages, including T-SQL and U-SQL.*
*- Additional tools like HDInsights, Azure Databricks for ETL, streaming, and working with data lakes.*
22:21 📊 *Common Tools for Data Analysts*
*- Power BI Desktop for data visualization and modeling.*
*- Power BI Service (Portal) for creating interactive dashboards.*
*- Power BI Report Builder for building paginated reports.*
23:46 📚 *Data Fundamentals Overview*
*- Understanding data as units of information.*
*- Categories like data documents, datasets, data types.*
*- Concepts of batch and streaming processing.*
24:29 📖 *Understanding Data*
*- Data encompasses various forms, including numbers, text, images, videos, audio, or even physical forms.*
*- Examples illustrating data types: binary code, books, audio spectrum, mathematical formulas.*
25:11 🗂 *Data Documents*
*- Definition and types like datasets, databases, data stores, data warehouses, and notebooks.*
*- Examples include MNIST and COCO datasets, highlighting structured and semi-structured data.*
26:08 📋 *Data Sets*
*- Logical grouping of related data units with examples like MNIST and COCO datasets.*
*- Publicly available datasets for learning statistics, analytics, and machine learning.*
28:41 🧮 *Data Types*
*- Numeric data types (integer, float), text data types (characters, strings).*
*- Composite data types (arrays, dictionaries) and binary data types.*
32:24 📐 *Schema vs. Schema-less*
*- Schema as a formal language describing data structure in databases.*
*- Schema-less offers flexibility, allowing more dynamic data without upfront modeling.*
34:14 ❓ *Querying Data*
*- Query as a request for data or performing operations like insert, update, delete.*
*- Data results, querying, query language (SQL, GraphQL, XQuery), and their importance.*
36:01 🔄 *Batch vs. Stream Processing*
*- Batch processing involves scheduled processing of data collections.*
*- Stream processing is real-time, processing data as it arrives.*
38:34 📊 *Relational Data*
*- Tables, views, materialized views, indexes, constraints, triggers, and primary keys.*
*- Explanation of primary keys as unique identifiers for rows in a table.*
40:09 🗃️ *Relational Database Relationships*
42:18 📊 *Row Store vs. Column Store*
43:58 📈 *Database Indexes*
45:18 🔄 *Data Integrity vs. Data Corruption*
47:15 🔄 *Normalized vs. Denormalized Data*
48:41 🔄 *Pivot Tables in Data Processing*
50:18 ⚖️ *Data Consistency: Strongly vs. Eventually Consistent*
51:41 🔄 *Synchronous vs. Asynchronous Data Transformation*
53:34 🗄️ *Non-Relational Data Stores*
54:42 🔄 *Data Sources and Connections*
55:53 🗃️ *Data Store Overview*
58:00 📊 *Data Warehouse*
01:00:48 🌊 *Data Lake*
01:01:02 📊 *Data Lakes Overview*
01:01:45 🏡 *Data Lake House Characteristics*
01:03:09 🧱 *Introduction to Data Structures*
01:04:03 🗂️ *Azure Services for Unstructured Data*
01:04:59 🧩 *Semi-Structured Data and Formats*
01:07:20 🌐 *JSON - Lightweight Data Interchange*
01:08:17 🚀 *Apache ORC Files - Optimized Row Columnar Format*
01:10:35 🏹 *Apache Avro - Compact, Fast Binary Format*
01:11:34 📊 *Structured Data Overview*
01:12:57 🛠️ *Data Mining Phases*
01:13:54 🔍 *Data Mining Methods*
01:14:49 🔗 *Data Wrangling Process*
01:15:33 🎨 *Data Modeling Overview*
01:17:25 🔄 *ETL vs. ELT*
01:19:16 📈 *Data Analytics Workflow*
01:20:14 🎯 *Key Performance Indicators (KPIs)*
01:20:57 🤔 *Data Analytics vs. Data Mining*
01:21:09 📊 *Descriptive, Diagnostic, Predictive, Prescriptive, Cognitive Analytics*
01:23:03 🏡 *Microsoft OneDrive Overview*
01:24:41 🏢 *Microsoft 365 SharePoint Features*
01:25:52 🧱 *Data Core Concepts: Data Types, Structures, and Roles*
01:27:59 📚 *Data Stores, Data Warehouses, Data Marts*
01:29:54 🧠 *Data Modeling, Integrity, Corruption, Normalization*
01:31:46 🔗 *Data Mining, Data Wrangling, Query, Data Source*
01:33:11 📊 *Data Analytics Types and Key Performance Indicators*
01:34:50 🏠 *Azure Synapse Analytics Overview*
01:35:32 🗃️ *Synapse SQL: Distributed T-SQL, Serverless, Dedicated Pools*
01:37:23 🔍 *Apache Spark, Data Lake Integration with Azure Synapse*
01:38:33 🌊 *Data Lake Overview, Azure Data Lake Storage Gen 2*
01:40:12 🔄 *PolyBase: Data Virtualization in SQL Server*
01:40:26 🔄 *ETL in Azure Synapse Analytics*
01:40:52 🔄 *Azure Synapse Analytics ETL Process*
01:41:46 📊 *Azure Data Lake Analytics and USQL*
01:43:23 🌐 *Azure Data Lake Storage and Azure Synapse Analytics*
01:44:15 ☁️ *Azure Blob Storage Overview*
01:45:58 📂 *Azure Files Use Cases*
01:47:49 🗃️ *Azure Storage Accounts Overview*
01:48:33 📊 *Business Intelligence Tools*
01:49:59 📊 *Microsoft Power BI Overview*
01:51:35 📈 *Data Visualizations in Power BI*
01:53:30 🛠️ *Power BI Embedded Overview*
01:54:54 🔄 *Power BI Interactive Reports*
01:56:49 📊 *Power BI Service and Dashboards*
02:00:02 📄 *Paginated Reports in Power BI*
02:00:29 📊 *SQL Fundamentals*
02:01:54 🔄 *OLAP vs. OLTP*
02:03:19 🗃️ *Open Source Relational Databases*
02:06:06 🔄 *Read Replicas for Azure Databases*
02:07:19 🌐 *Citus on Azure*
02:08:15 💻 *Azure SQL Family*
02:10:39 🔄 *Azure Elastic Pools*
02:11:51 📄 *Relational Database Cheat Sheet*
02:15:42 📚 *Data Definition Language (DDL)*
02:16:51 🔄 *Data Manipulation Language (DML)*
02:18:15 📖 *Data Query Language (DQL)*
02:19:14 🔐 *Data Control Language (DCL)*
02:19:44 ⚙️ *Transaction Control Language (TCL)*
02:19:58 🔄 *Transaction Concepts in SQL*
02:21:11 📑 *Overview of T-SQL (Transact-SQL)*
02:22:08 🌐 *Connectivity Architecture in Azure SQL Database*
02:23:18 🔐 *MS SQL Database Authentication Modes*
02:24:44 🌐 *Network Connectivity Options in SQL Database*
02:25:26 🛡️ *Azure Defender for SQL*
02:26:09 🚧 *Azure Database Firewall Rules*
02:27:04 🔒 *Always Encrypted in Azure SQL Database*
02:27:49 👤 *Role-Based Access Control for Databases*
02:28:59 🌐 *Transparent Data Encryption (TDE) in Microsoft Databases*
02:29:56 🎭 *Dynamic Data Masking in Azure SQL Servers*
02:31:12 🌐 *Azure Private Links for Secure Connections*
02:31:57 🌐 *Introduction to Database Security for Azure*
02:35:42 📄 *Document Stores for Structured Data*
02:36:38 🍃 *MongoDB: Open Source Document Database*
02:38:42 🌐 *Graph Databases: Modeling Relationships*
02:39:48 🔄 *Azure TinkerPop: Graph Computing Framework*
02:40:02 📊 *Graph Databases Overview*
02:41:24 🗃️ *Azure Tables - Storage for NoSQL Key-Value Data*
02:42:49 🔄 *CosmosDB Overview*
02:44:40 🔄 *Azure Tables vs. CosmosDB Comparison*
02:46:51 📋 *Azure Tables and CosmosDB Cheat Sheet*
02:52:05 📊 *Apache Hadoop and HDInsight Overview*
02:53:15 📋 *Apache Spark and Databricks Cheat Sheet*
02:55:09 🛠️ *SQL Management Studio (SSMS) and Databricks Overview*
02:58:56 📊 *SQL Management Studio (SSMS) Overview*
02:59:38 🛠️ *Azure Server Data Tools (SSDT)*
03:01:03 🌐 *Azure Data Studio Features*
03:01:43 🚀 *Azure Data Factory*
03:02:57 📊 *SQL Server Integration Services (SSIS)*
03:04:23 📊 *ETL and SQL Tools Cheat Sheet*
03:05:47 🖥️ *Installing Power BI*
03:08:28 🌐 *Azure SQL Overview*
03:11:43 🚀 *Provisioning Azure SQL Database*
03:15:08 🔒 *Azure SQL Security Features*
03:18:10 🛠️ *Connecting to Azure SQL*
03:18:37 💻 *Database Setup in Azure Data Studio*
03:23:17 📊 *Installation of Azure Data Studio and Query Execution*
03:25:26 🖥️ *Connecting Power BI to SQL Server*
03:34:54 📈 *Visualization in Power BI Desktop*
03:38:56 🚀 *Publishing to Power BI Service*
03:39:11 📊 *Power BI Overview*
03:44:19 📊 *Power BI Dashboard Creation*
03:47:37 🛠️ *SQL Server Management Studio (SSMS)*
03:57:38 ☁️ *Azure Storage Accounts*
03:57:38 🔄 *Cosmos DB - Core SQL*
03:57:38 🔄 *Cosmos DB - MongoDB*
03:57:38 🔄 *Cosmos DB - Azure Table*
03:57:38 🔄 *Cosmos DB - Gremlin*
04:00:30 🚀 *Overview of Azure Cosmos DB and Quick Start with SQL API*
04:08:50 📊 *Setting Up MongoDB with Cosmos DB*
04:16:34 📑 *Working with Azure Tables in Cosmos DB*
04:18:29 🌀 *Introduction to Gremlin API in Cosmos DB*
04:23:21 📈 *Visualizing Graph Data in Cosmos DB with Gremlin API*
04:23:43 📊 *Azure Cosmos DB and Gremlin Query Language*
04:27:10 🔄 *Data Factory for SQL to Blob Storage Transformation*
04:33:07 🚀 *Introduction to Azure Databricks*
04:39:49 📈 *Azure Synapse Analytics (formerly SQL Data Warehouse)*

Made with HARPA AI

[JuninhoSantosPlus]

Thanks Andrew! I was able to pass in the exam in the first attempt! Great content! You rock!

[fvze]

i passed the exam and got 833 from watching this course + training module from microsoft.
great video with cheat set ...
thank you so much...

[decembernightlights]

Please UPDATE (DP-900) Microsoft Azure Data Fundamentals. It's been 3 Years.

[hdsheena]

I took the webinar a couple weeks ago so qualify for the test, but the info wasn’t clear on how long the webinar was, so I missed some. So grateful to find this!

[StanfordDsilva]

Thank you Andrew. Appreciate the effort you have put in to make these videos.

[ashishmishra]

Very Informative and well explained. Please share tutorial for DP-203: Data Engineering on Microsoft Azure.
Thank you Andrew.

[eradubbo]

Just passed! Thank you for a great course.

[anand]

Andrew you're a super man...need tutorial for DP 203

[munivenkatashyamsundarkami]

Hello Brown,
I have passed DP-900 with help of This Vidio. All Concepts were Clear to Frame Connectivity and understanding How Cocepts work.
Thank you.

[TheGeekSurgeon]

Andrew Thank you for the resource you have provided I passed 9_21_21. This is my first step to becoming a data scientist. Thank you.