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

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    Prepare for the Azure Data Fundamentals Certification and pass!

    โœ๏ธ Course developed by Andrew Brown of ExamPro. Check out the ExamPro YouTube channel: https://www.youtube.com/ExamProChannel
    ๐Ÿ”— ExamPro Cloud Obsessed Certification Training: https://www.exampro.co

    โ˜๏ธ Data Concepts
    ๐ŸŽค (0:10:12) Auzre Core Data Related Services
    ๐ŸŽค (0:14:55) Types of Cloud Computing
    ๐ŸŽค (0:16:56) Azure Data Related Roles
    ๐ŸŽค (0:18:42) Database Administrator Common tools
    ๐ŸŽค (0:20:27) Data Engineering Common tools
    ๐ŸŽค (0:21:43) Data Analyst Common tools
    ๐ŸŽค (0:22:26) Data Overview
    ๐ŸŽค (0:23:43) Introduction to Data
    ๐ŸŽค (0:24:32) Data documents
    ๐ŸŽค (0:25:30) Data sets
    ๐ŸŽค (0:28:31) Data types
    ๐ŸŽค (0:32:15) Schema vs Schemaless
    ๐ŸŽค (0:34:09) Query and Querying
    ๐ŸŽค (0:35:54) Batch vs Stream processing
    ๐ŸŽค (0:38:30) Relational data
    ๐ŸŽค (0:40:35) Relational data Relationships
    ๐ŸŽค (0:42:07) Row store vs Column store
    ๐ŸŽค (0:43:44) Database Index
    ๐ŸŽค (0:45:05) Data Integegrity vs Data Corruption
    ๐ŸŽค (0:47:11) Normalized vs Denomralized data
    ๐ŸŽค (0:48:32) Pivot table
    ๐ŸŽค (0:50:10) Strongly consistent vs Eventually consistent
    ๐ŸŽค (0:51:33) Synchronus vs Asynchronous
    ๐ŸŽค (0:53:29) Non relational data
    ๐ŸŽค (0:54:29) Data source
    ๐ŸŽค (0:55:41) Data store
    ๐ŸŽค (0:56:32) Database
    ๐ŸŽค (0:57:56) Data warehouse
    ๐ŸŽค (0:59:39) Data mart
    ๐ŸŽค (1:00:36) Data lakes
    ๐ŸŽค (1:01:42) Data lakehouse
    ๐ŸŽค (1:03:12) Data structures
    ๐ŸŽค (1:04:02) Unstructured data
    ๐ŸŽค (1:04:47) Semi structured
    ๐ŸŽค (1:06:10) Semi structured Data Structures
    ๐ŸŽค (1:07:16) Semi structure JSON
    ๐ŸŽค (1:08:11) semi structure ORC
    ๐ŸŽค (1:09:39) semi structure Parquets
    ๐ŸŽค (1:10:35) semi structure AVRO
    ๐ŸŽค (1:11:25) Structured Data
    ๐ŸŽค (1:11:56) Data mining
    ๐ŸŽค (1:13:02) Data mining methods
    ๐ŸŽค (1:14:28) Data wrangling
    ๐ŸŽค (1:15:31) Ddata modeling
    ๐ŸŽค (1:17:18) ETL vs ELT
    ๐ŸŽค (1:19:18) Data analytics
    ๐ŸŽค (1:20:14) Key performance indicators KPI
    ๐ŸŽค (1:21:23) Data Analytic Techniques
    ๐ŸŽค (1:23:02) Microsoft One Drive
    ๐ŸŽค (1:24:20) Microsoft Sharepoint
    ๐ŸŽค (1:25:49) Data Core Concepts CheatSheet

    โ˜๏ธ Azure Synapse and Data Lake
    ๐ŸŽค (1:33:36) Azure Synapse Analytics
    ๐ŸŽค (1:35:26) Sypanse SQL and pools
    ๐ŸŽค (1:37:19) Synapse Key Features
    ๐ŸŽค (1:38:31) Azure Data Lake Gen 2
    ๐ŸŽค (1:40:03) Polybase
    ๐ŸŽค (1:40:50) Synapse ELT
    ๐ŸŽค (1:41:51) Azure Data Lake Analytics
    ๐ŸŽค (1:43:05) Azure Sypanse and Data Lakes CheatSheet

    โ˜๏ธ Account Storage
    ๐ŸŽค (1:44:25) Azure Blob Storage
    ๐ŸŽค (1:45:20) Azure Files
    ๐ŸŽค (1:47:14) Azure Storage Accounts CheatSheet

    โ˜๏ธ Power BI
    ๐ŸŽค (1:48:07) Business Intelligence
    ๐ŸŽค (1:48:40) Power BI
    ๐ŸŽค (1:51:29) Power BI Visualizations
    ๐ŸŽค (1:53:13) Power BI Embedded
    ๐ŸŽค (1:54:02) Power BI Interactive Reports
    ๐ŸŽค (1:55:36) Power BI Service and Dashboards
    ๐ŸŽค (1:56:47) Reports vs Dashboards
    ๐ŸŽค (1:57:47) Paginated Reports
    ๐ŸŽค (1:58:57) Power BI CheatSheet

    โ˜๏ธ Relational Databases
    ๐ŸŽค (2:00:38) Structured Query Language
    ๐ŸŽค (2:01:48) OLAP vs OLAP
    ๐ŸŽค (2:03:14) Open Source Relational Databases
    ๐ŸŽค (2:06:01) Read Replicas
    ๐ŸŽค (2:07:10) Citus Postgres Hyperscale
    ๐ŸŽค (2:08:03) Azure SQL Family
    ๐ŸŽค (2:10:30) Elastic pools
    ๐ŸŽค (2:11:45) Relational Databases CheatSheet

    โ˜๏ธ T SQL
    ๐ŸŽค (2:14:12) T SQL
    ๐ŸŽค (2:15:40) Data Defintion Language
    ๐ŸŽค (2:16:43) Data Manipulation Language
    ๐ŸŽค (2:18:02) Data Query Language
    ๐ŸŽค (2:19:08) Data Control Language
    ๐ŸŽค (2:19:36) Transaction Control Langauge
    ๐ŸŽค (2:20:22) SQL Document Comparsions
    ๐ŸŽค (2:21:10) T SQL CheatSheet

    โ˜๏ธ Database Security
    ๐ŸŽค (2:22:01) Connectivity Architecture
    ๐ŸŽค (2:23:13) Database Authentication
    ๐ŸŽค (2:24:41) Network Connectivity
    ๐ŸŽค (2:25:19) Azure Defender for SQL
    ๐ŸŽค (2:25:54) Azure Database Server Firewalls
    ๐ŸŽค (2:27:00) Always Encrypted
    ๐ŸŽค (2:27:47) Role Based Access Controls
    ๐ŸŽค (2:28:48) Transparent Data Encryption
    ๐ŸŽค (2:29:49) Dynamic Data Masking
    ๐ŸŽค (2:31:02) Private Links
    ๐ŸŽค (2:31:57) Database Security Cheatsheet

    โ˜๏ธ Azure Tables Cosmos DB
    ๐ŸŽค (2:34:13) Key Value Store
    ๐ŸŽค (2:35:40) Document Store
    ๐ŸŽค (2:36:33) Mongo DB
    ๐ŸŽค (2:38:35) Graph Database
    ๐ŸŽค (2:39:42) Apache Tinkerpop and Gremlin
    ๐ŸŽค (2:41:23) Azure Tables
    ๐ŸŽค (2:42:45) Azure Cosmos DB
    ๐ŸŽค (2:44:40) Azure Table Account Storage vs Cosmos DB
    ๐ŸŽค (2:46:39) Azure Tables and CosmosDB CheatSheet

    โ˜๏ธ Hadoop Systems
    ๐ŸŽค (2:48:29) Apache Hadoop
    ๐ŸŽค (2:49:57) Apache Kafka
    ๐ŸŽค (2:50:53) HDInsights
    ๐ŸŽค (2:52:05) Hadoop CheatSheet

    โ˜๏ธ Azure and Databricks
    ๐ŸŽค (2:53:21) Apache Spark
    ๐ŸŽค (2:55:04) Azure Databricks
    ๐ŸŽค (2:57:16) Apache Spark and Databricks CheatSheet

    โ˜๏ธ ELT and SQL Tools
    ๐ŸŽค (2:58:46) SQL Server Management Studio
    ๐ŸŽค (2:59:37) SQL Server Data Tools
    ๐ŸŽค (3:00:58) Azure Data Studio
    ๐ŸŽค (3:01:48) Azure Data Factory
    ๐ŸŽค (3:02:59) SQL Server Integration Services
    ๐ŸŽค (3:04:08) ETL and SQL Tools CheatSheet

    โ˜๏ธ Follow Alongs
    ๐ŸŽค (3:05:38) Install and Use Power BI
    ๐ŸŽค (3:08:17) Launch Azure SQL and Use Data Studio
    ๐ŸŽค (3:34:53) Use Azure SQL as data source in Power BI
    ๐ŸŽค (3:44:20) Use SSMS to perform a query on Azure SQL
    ๐ŸŽค (3:47:37) Create Blob and File storage
    ๐ŸŽค (3:57:36) Explore CosmosDB various NoSQL engines
    ๐ŸŽค (4:27:08) Create a ELT job from Azure SQL to Blob Storage
    ๐ŸŽค (4:33:06) Explore Azure Databricks
    ๐ŸŽค (4:39:49) Explore Azure Synapse Analytics
    ๐ŸŽค (4:44:47) Cleanup

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    40 COMMENTS

    1. Taking the test tomorrow. Watched the whole series – admittedly at mostly 0.75x – looking forward to posting back on success. A whole career of MSSQL, a few years of HDinsights, a couple of hours on Cosmos, and a few years of detached hadoop. I should've been looking into resources like this for a long time, nice refresher.