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Exam DP-900 Microsoft Azure Data Fundamentals (Video)

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Exam DP-900 Microsoft Azure Data Fundamentals (Video)

Online Video

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Description

  • Copyright 2022
  • Edition: 1st
  • Online Video
  • ISBN-10: 0-13-757669-2
  • ISBN-13: 978-0-13-757669-2

4+ Hours of Video Instruction

Prepare for Microsoft Exam DP-900 and demonstrate your knowledge of fundamental data concepts and Microsoft Azure data services.

Description

This Exam DP-900: Microsoft Azure Data Fundamentals video is designed to help you begin to work with data in the cloud. This video focuses on the skills measured by the exam objectives, as updated by Microsoft in April 2021.

  • Describe core data concepts
  • Describe how to work with relational data on Azure
  • Describe how to work with non-relational data on Azure
  • Describe an analytics workload on Azure


Using his years of experience working with data and teaching data best practices to a variety of learners, Microsoft Certified Trainer Chris Sorensen explains core concepts related to working with data in Azure. In his engaging style grounded in real-world scenarios, Chris gives you insights to relational and non-relational data, different types of workloads, and analytical best practices. With Chris as your guide, you are well-equipped to successfully attempt the DP-900 exam and advance in your career as a data engineer or database administrator.

Skill Level
  • Beginner to Intermediate


Who Should Take This Course
  • Certification candidates preparing for exam DP-900 Microsoft Azure Data Fundamentals
  • Analysts or admins beginning to work with data in the cloud


Course Requirements
  • Foundational knowledge of core data concepts


About Pearson Video Training

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.

Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.

Sample Content

Table of Contents

Introduction

Module 1: Describe Core Data Concepts
Lesson 1: Describe Types of Core Data Workloads
Learning objectives
1.1 Describe batch data
1.2 Describe streaming data
1.3 Describe the difference between batch and streaming data
1.4 Describe the characteristics of relational data
Lesson 2: Describe Data Analytics Core Concepts
Learning objectives
2.1 Describe data visualization
2.2 Describe basic chart types
2.3 Describe analytics techniques
2.4 Describe ELT and ETL processing
2.5 Describe the concepts of data processing

Module 2: Describe How to Work with Relational Data on Azure
Lesson 3: Describe Relational Data Workloads
Learning objectives
3.1 Identify the right data offering for a relational workload
3.2 Describe relational data structures
Lesson 4: Describe Relational Azure Data Services
Learning objectives
4.1 Describe Azure SQL family of products
4.2 Describe Azure Synapse Analytics
4.3 Describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL
Lesson 5: Identify Basic Management Tasks for Relational Data
Learning objectives
5.1 Describe provisioning and deployment of relational data services
5.2 Describe method for deployment
5.3 Identify data security components
5.4 Identify basic connectivity issues
Lesson 6: Describe Query Techniques for Data Using SQL Language
Learning objectives
6.1 Compare Data Definition Language (DDL) versus Data Manipulation Language (DML)
6.2 Query relational data in Azure
Module 3: Describe How to Work with Non-Relational Data on Azure
Lesson 7: Describe Non-Relational Data Workloads
Learning objectives
7.1 Describe the characteristics of non-relational data
7.2 Describe the types of non-relational and NoSQL data
7.3 Recommend the correct data store
7.4 Determine when to use non-relational data
Lesson 8: Describe Non-Relational Data Offerings on Azure
Learning objectives
8.1 Identify Azure data services for non-relational workloads
8.2 Describe Azure Cosmos DB APIs
8.3 Describe Azure Table Storage
8.4 Describe Azure Blob Storage
8.5 Describe Azure File Storage
Lesson 9: Identify Basic Management Tasks for Non-Relational Data
Learning objectives
9.1 Describe provisioning and deployment of non-relational data services
9.2 Describe method for deployment
9.3 Identify data security components
9.4 Identify basic connectivity issues
9.5 Identify management tools for non-relational data
Module 4: Describe an Analytics Workload on Azure
Lesson 10: Describe Analytics Workloads
Learning objectives
10.1 Describe transactional workloads
10.2 Describe the difference between a transactional and an analytics workload
10.3 Describe the difference between batch and real time
10.4 Describe data warehousing workloads
10.5 Determine when a data warehouse solution is needed
Lesson 11: Describe the Components of a Modern Data Warehouse
Learning objectives
11.1 Describe Azure data services for modern data warehousing
11.2 Describe modern data warehousing architecture and workload
Lesson 12: Describe Data Ingestion and Processing on Azure
Learning objectives
12.1 Describe common practices for data loading
12.2 Describe the components of Azure Data Factory
12.3 Describe data processing options
Lesson 13: Describe Data Visualization in Microsoft Power BI
Learning objectives
13.1 Describe the workflow in Power BI
13.2 Describe the role of interactive reports
13.3 Describe the role of dashboards
13.4 Describe the role of paginated reporting
Summary

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