Dp-900: Microsoft Azure Data Fundamentals Course - May 2022

DP-900: Microsoft Azure Data Fundamentals || 10+ hrs of videos || 100% Syllabus Covered || 200+ Ques + 2 Practice Tests

What you'll learn

Students will be prepared for the DP-900 certification exam

Learn types of core data workloads concepts

Learn basics of 4 types of NoSQL databases and implementation NoSQL on Azure Platform (Cosmos DB APIs, Table, Blob and File storage)

Learn diff Relational databases and implementation on Azure (Azure SQL Database and Managed Instance)

Learn analytics workloads, including data warehouses, data ingestion and processing on Azure

Describe data visualization in Microsoft Power BI, including reports and dashboards

Requirements

This is basic course and so no prerequisite is required

However previous database knowledge or experience would help student to understand course quickly

Description

The Microsoft Azure DP-900 exam is the best example of a basic level of qualification to prove your knowledge of core data services and Microsoft Azure data services. Applicants are looking for accurate information on the preparation of DP-900 exams due to the favorable job opportunities associated with Microsoft Azure details.Exam Name:  Exam DP-900: Microsoft Azure Data FundamentalsExam Duration 60 MinutesExam Type Multiple Choice ExaminationNumber of Questions 40 - 60 QuestionsExam Fee $99 (Depends on Country)Eligibility/Pre-requisite NoneExam validity LifetimeExam Languages English, Japanese, Korean, and Simplified ChineseAreas CoveredDescribe types of core data workloads, batch and streaming data, and core concepts of data analytics.Describe relational data workloads, relational Azure data services such as comparing PaaS, IaaS, and SaaS delivery models.Identify basic management tasks for relational data including provisioning and deployment of relational data services and describing query techniques for data using SQL language.Describe non-relational data workloads and non-relational data offerings on Azure and describe provisioning and deployment of non-relational data services.Describe analytics workloads and components of a modern data warehouseDescribe data ingestion and processing on Azure and data visualization in Microsoft Power BIDomains Covered in DP-900 ExamAnother significant factor that all candidates should consider for the successful training of the DP-900 exam is the overview of the exam skills. Applicants with a better understanding of the exam topics and weighting of the exam domains can gain a general impression of the exam prior to their preparation. The following topics can be found in the DP-900 certification test.Describing core data concepts- 15% to 20%Describe the approaches to work with relational data on Azure- 25% to 30%Describing approaches to work with non-relational data on Azure- 25% to 30%Description of an Azure analytics workload- 25% to 30%The preparation guide for the DP-900 exam can become better with an outline of the subtopics covered in each domain. Here is a reflection on the subtopics you can find in different domains of the DP-900 certification exam.Domain 1: Describing core data conceptsThe subtopics in this domain are,Describing types of core data workloads.Describing core concepts of data analytics.Domain 2: Describe the approaches to work with relational data on AzureThe subtopics in this domain are,Description of relational data workloads.Description of relational Azure data services.Identification of basic management tasks for relational data.Description of query techniques for data by leveraging SQL language.Domain 3: Describing approaches to work with non-relational data on AzureThe subtopics in this domain are,Describing non-relational data workloads.Describing non-relational data offerings on Azure.Identification of basic management tasks for non-relational data.Domain 4: Description of an Azure analytics workloadThe subtopics in this domain are,Describing analytics workloads.Describing the components of a modern data warehouse.Description of data ingestion and processing on Azure.Describing data visualization in Microsoft Power BI.

Overview

Section 1: Introduction

Lecture 1 IMP Note: Course Update - 29th April 2022

Lecture 2 IMP - Instructions

Lecture 3 Course Introduction

Lecture 4 IMP: Everything you need to know about exam and this course

Lecture 5 PPT and Demo Resources

Lecture 6 Before you start…

Section 2: Azure Portal Introduction

Lecture 7 Create Azure Free Subscription

Lecture 8 Azure Portal Overview

Lecture 9 IaaS vs PaaS vs SaaS

Lecture 10 Azure Sandbox - How to use Azure Portal for absolutely free

Lecture 11 How to get FREE credits for Azure Portal

Lecture 12 Further Reading

Section 3: Describe core data concepts

Lecture 13 Introduction and Learning Objectives

Lecture 14 Data Types

Lecture 15 Different Files Formats

Lecture 16 Transaction (OLTP) vs Analytics (OLAP) workload

Lecture 17 Roles and Responsibilities for Data Workloads

Lecture 18 Data Processing Solutions (OLTP vs OLAP)

Lecture 19 Describe the concepts of Data Processing

Lecture 20 ETL vs ELT

Lecture 21 Further Study Material

Section 4: Describe how to work with relational data on Azure

Lecture 22 Characteristics of Relational Database

Lecture 23 Notes: Relational Database

Lecture 24 Describe Relational DB structures

Lecture 25 Provisioning and Deployment in Azure

Lecture 26 Methods of Provisioning

Lecture 27 Why choosing SQL Database in Azure

Lecture 28 Azure IaaS vs PaaS database offerings

Lecture 29 SQL Database PaaS Deployment Options

Lecture 30 Azure SQL Server in Virtual Machine (IaaS)

Lecture 31 Azure SQL Database vs Data Warehouse

Lecture 32 Demo: Azure Single SQL Server Database and Firewall Settings

Lecture 33 Open Source DB: PostgreSQL, MariaDB and MySQL

Lecture 34 Identify Query Tools

Lecture 35 Introduction to SQL

Lecture 36 Demo: SQL SELECT Query

Lecture 37 Identify the right data offering for a relational workload

Lecture 38 Further Study Material

Section 5: Describe how to work with non-relational data on Azure

Lecture 39 Introduction and Learning Objectives

Lecture 40 Introduction to NoSQL

Lecture 41 SQL vs NoSQL

Lecture 42 4 types of NoSQL Databases

Lecture 43 JSON File Structure

Lecture 44 NoSQL Offerings by Microsoft Azure

Lecture 45 Azure Storage Services Overview

Lecture 46 Demo Provision Azure Storage Account

Lecture 47 Data Redundancy Options

Lecture 48 Azure Blob Storage

Lecture 49 Azure Storage Access Tiers

Lecture 50 Azure Table Storage

Lecture 51 Azure File Share Storage

Lecture 52 Demo Azure File Share Storage

Lecture 53 How Cosmos DB evolved?

Lecture 54 Cosmos DB Features

Lecture 55 Cosmos DB Multi Model 5 APIs

Lecture 56 Provision Cosmos DB Account

Lecture 57 Cosmos DB: Globally Distribution

Lecture 58 Further Study Material

Section 6: Describe an analytics workload on Azure

Lecture 59 Introduction and Learning Objectives

Lecture 60 What is Data Warehouse

Lecture 61 Why we need Data Warehouse

Lecture 62 Star Schema - Fact/Dimension

Lecture 63 Why Warehousing in Cloud

Lecture 64 Modern Data Warehouse Architecture

Lecture 65 What is Azure Synapse Analytics Service

Lecture 66 What is HDInsight

Lecture 67 Batch Processing

Lecture 68 Real Time Processing

Lecture 69 Azure Stream Analytics

Lecture 70 Batch Processing vs Stream Processing

Lecture 71 What is Data Lake

Lecture 72 Data Lake Gen2 Hierarchical namespace

Lecture 73 What is Data Factory

Lecture 74 Provision Azure Data Factory Instance

Lecture 75 Data Factory - Components

Lecture 76 Data Factory Components Relation

Lecture 77 Data Factory Triggers

Lecture 78 What is Azure Databricks

Lecture 79 Azure Data Service Architecture

Lecture 80 Introduction to PowerBI

Lecture 81 Building Blocks of Power BI

Lecture 82 PowerBI: Role of Dashboard

Lecture 83 Power BI: Workflow

Lecture 84 Data Visualization and Chart Types

Lecture 85 Further Study Material

Section 7: Practice Tests

Lecture 86 Note about Practice Tests

Lecture 87 More Practice Questions

Section 8: RETIRED on 29th April 2022

Lecture 88 Notes: Batch vs Stream Processing

Lecture 89 Data Analytics Techniques

Lecture 90 Notes: Data Analytics Techniques

Lecture 91 Azure Relational Database Security Layers

Lecture 92 Azure Database for MySQL

Lecture 93 Visual Studio Code

Lecture 94 Azure Queue Storage

Lecture 95 Azure Disk Storage and demo

Lecture 96 Azure Blob and Data Lake Security Options

Lecture 97 MPP Architecture - Synapse Analytics Service

Lecture 98 Different loading methods

Lecture 99 Cosmos DB: Multi Master

Lecture 100 Cosmos DB: 5 consistent level

Lecture 101 Cosmos DB: Security

Lecture 102 Demo: Insert and query data in Your cosmos DB

Lecture 103 Identify management tools for non-relational data

Lecture 104 No SQL Deployment Options

Lecture 105 Paginated Report

Lecture 106 Interactive Report

Section 9: Wrapping up

Lecture 107 What's Next?

Lecture 108 Bonus Section

Those who want to pass the Microsoft exam DP-900,Those who want to enter in to Azure Cloud Data related profiles like Data Engineer, Data Scientist, Data Analyst etc