What you'll learn
Understand types of core data workloads and data analytics core concepts
Understand how to work with relational data on Azure, including Azure SQL Database and Managed Instance
Understand how to work with non-relational data on Azure, including Cosmos DB APIs, Table, Blob and File storage
Describe analytics workloads, including data warehouses, data ingestion and processing on Azure
Describe data visualization in Microsoft Power BI, including reports and dashboards
Requirements
You need to know how to use a computer, and hopefully know how to use a spreadsheet.
No prior knowledge of databases required.
All of the programs used can be installed on Windows, and some can be installed on macOS.
There is a 30-day refund guarantee of this Udemy course (see Udemy's refund policy).
Why not have a look at the curriculum below and see what you can learn?
Description
This course is the foundation for the Microsoft Certificate DP-900 "Azure Data Fundamentals", and focuses on relational and non-relational data, together with analytics workloads. It is updated in line with the exam updates as of August 4, 2022.What do people like you say about this course?Girma says: "Great! – Azure would never be difficult (as most of us think) after thoroughly going through this course."Ankona says: "Very good course. Philip proves why is indeed the go to guy for everything to do with databases. I have taken a couple of his courses on various aspects of databases and he never disappoints."Karen says: "This course helped me to clear the exam with 903."We'll start off with looking at relational data. We'll create an Azure account, install an Azure SQL Database and query it. We'll then look at the 6 different clauses of the SELECT statement - SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY. After this, we'll have a look at other relational databases, including Azure Databases for PostgreSQL, MariaDB and MySQL.After that, we'll look at non-relational data using semi-structured and non-structured data. We'll look at the five different Cosmos DB database interfaces or APIs, and which one you should use for your particular needs. We'll also look at Table, Blob and File storage. We'll then look at analytics workloads, including Azure data services for modern data warehouses such as Azure Data Lake, Synapse Analytics, Databricks and HDInsight.Finally, we'll look at Microsoft Power BI and how to create basic reports and dashboards.No prior knowledge is required - we'll even see how to get a free Azure trial!There are regular quizzes to help you remember the information, so you can be sure that you are learning.Once you have finished this course, you will have a good introductory knowledge of core data concepts and how they are implemented using Microsoft Azure data services. And with some practice, you could even go for an official Microsoft certification - wouldn't that look good on your CV or resume? And if you are an American college student, you might even get college credit for passing that exam.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Welcome to Udemy
Lecture 3 The Udemy Interface
Lecture 4 Do you want auto-translated subtitles in more languages?
Lecture 5 Curriculum
Lecture 6 Let's have a Udemy Mashup!
Lecture 7 Resources
Section 2: Let's start using Microsoft Azure
Lecture 8 What is Azure
Lecture 9 Creating an Azure account
Lecture 10 15. Install Azure SQL Database with sample data
Section 3: Creating SELECT statements
Lecture 11 13. Query relational data in PostgreSQL, MySQL, and Azure SQL Database - SELECT
Section 4: Programs used for querying relational data
Lecture 12 Programs used for querying relational data: SQL Server Management Studio
Lecture 13 Programs used for querying relational data: Azure Data Studio
Lecture 14 Differences between SSMS and Azure Data Studio
Section 5: Describe relational data workloads
Lecture 15 1, 11, 12. Describe the characteristics of relational data - Tables
Lecture 16 1, 11, 12. Describe the characteristics of relational data - Normalization
Lecture 17 1, 11, 12. Characteristics of relational data - Primary and Foreign Keys
Lecture 18 14. Describe relational data structures: Indexes
Lecture 19 14. Describe relational data structures: Views
Lecture 20 14. Other relational data structures
Section 6: Describe relational Azure data services - SQL Server
Lecture 21 On Prem versus the Cloud
Lecture 22 Describe and compare PaaS, IaaS, and SaaS delivery models
Lecture 23 15. Creating Azure SQL Database (in detail) - Part 1 (including Regions)
Lecture 24 15. Creating Azure SQL Database - Elastic Pools, compute and storage
Lecture 25 15. Creating Azure SQL Database - other settings
Lecture 26 15. Describe Azure SQL Managed Instance
Lecture 27 15. Describe SQL Server on Azure Virtual Machine
Section 7: Describe relational Azure data services - Other Azure relational Databases
Lecture 28 16. Describe Azure Database for PostgreSQL
Lecture 29 16. Describe Azure Database for MySQL
Lecture 30 16. Describe Azure Database for MariaDB
Lecture 31 4, 5. Identify the right data offering for a relational workload
Lecture 32 8-10. Identify roles and responsibilities for data workloads
Section 8: Non-relational Data - Semi-structured Data
Lecture 33 2, 3. Non-relational data - an introduction
Lecture 34 20, 21. Azure Cosmos DB APIs - Creating a Core (SQL) Cosmos DB
Lecture 35 20, 21. Azure Cosmos DB APIs - Querying a Core (SQL) Cosmos DB
Lecture 36 20, 21. Replicating Data Globally
Lecture 37 20, 21. Azure Cosmos DB APIs - Gremlin API (Graph)
Lecture 38 20, 21. Other Azure Cosmos DB APIs
Lecture 39 4, 5. Recommend the correct data store
Section 9: Describe non-relational data offerings on Azure
Lecture 40 Storage Accounts
Lecture 41 Replication Options
Lecture 42 19. Describe Azure Table storage
Lecture 43 17. Creating and uploading to Azure Blob storage
Lecture 44 17. Accessing and assigning access tiers to BLOB Storage
Lecture 45 18. Describe Azure File storage
Section 10: Describe analytics workloads
Lecture 46 6. What is a transaction?
Lecture 47 6. Describe transactional workloads: ACID, Locks and Distributed Databases
Lecture 48 22. Describe data warehousing workloads: Ingestion and common practices
Lecture 49 25. Describe the difference between batch and real time (streaming)
Lecture 50 7. Describe the difference between a transactional and an analytics workload
Section 11: Describe the components of a modern data warehouse
Lecture 51 Azure Data Factory and concepts of data processing
Lecture 52 SQL Server Integration Services (SSIS)
Lecture 53 Azure Data Lake
Lecture 54 24b. Azure Databricks
Lecture 55 26b. Azure Synapse Data Explorer
Lecture 56 24a. Azure Synapse Analytics
Lecture 57 26c. Spark structured streaming
Lecture 58 SQL Server Analysis Services (SSAS)
Lecture 59 24c. Azure HDInsight
Section 12: Describe data visualization in Microsoft Power BI
Lecture 60 27. Identify capabilities of Power BI
Lecture 61 28. Describe the workflow in Power BI
Lecture 62 27. Describe the role of interactive reports
Lecture 63 29. Describe basic chart types such as bar charts and pie charts
Lecture 64 29. Advanced Chart Types
Lecture 65 27. Describe the role of paginated reporting
Lecture 66 27. Describe the role of dashboards
Section 13: Congratulations
Lecture 67 You've finished this course - what should you do to prepare for the exam?
Lecture 68 Well done
Section 14: Additional - Describe query techniques for data using SQL language
Lecture 69 No longer needed for DP-900 exam
Lecture 70 Programs used for querying relational data: sqlcmd
Lecture 71 Programs used for querying relational data: Excel and Visual Studio
Lecture 72 Compare Data Definition Language DDL versus Data Manipulation Language DML
Section 15: Additional - Identify basic management tasks for relational data
Lecture 73 Describe provisioning and deployment of relational data services
Lecture 74 Identify data security components and connectivity issues
Lecture 75 Authentication and Authorization
Section 16: Additional - Identify basic management tasks for non-relational data
Lecture 76 Identify management tools for non-relational data
Lecture 77 Describe provisioning and deployment of non-relational data services
Lecture 78 Describe method for deployment
Lecture 79 Identify data security components and basic connectivity issues
Section 17: Additional - Analytics workloads and Power BI
Lecture 80 Describe ELT and ETL processing
Lecture 81 Determine when a data warehouse solution is needed
Lecture 82 Describe modern data warehousing architecture and workload
Lecture 83 Describe analytics techniques
Section 18: Bonus Lecture
Lecture 84 Bonus Lecture
This course is for you if you use data, and want to understand what is available on Azure.,By the end of this course, after entering the official Practice Tests, you could enter (and hopefully pass) Microsoft's official DP-900 exam.,Wouldn't the "Microsoft Certified: Azure Data Fundamentals" certification look good on your CV or resume?


Homepage

https://www.udemy.com/course/dp-900-microsoft-azure-data-fundamentals-course/