Course Overview

This DP-900 certification course from CloudThat is designed to help candidates pass the Microsoft DP-900 certification exam. This DP-900 exam is ideal for candidates beginning to work with data in the Cloud. Candidates taking up this training learn about the core data concepts and related Microsoft Azure data services. Before taking up this Microsoft Azure Data Fundamentals certification, candidates must be familiar with the relational and non-relational data concepts and the different types of data workloads, including transactional or analytical. Candidates can use the Azure Data Fundamentals certification to prepare for other Azure role-based certifications like Azure Data Engineer Associate or Azure Database Administrator Associate. However, it is not a prerequisite for any of them.

After completing this course, students will be able to:

  • To understand and build AI solutions on Azure
  • To learn about various Azure Machine Learning services usage & integration
  • To understand the profound impacts Machine Learning is making in smart business decisions

Upcoming Batches

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To be Decided

Key Features

  • Our Azure Data Fundamentals training modules have 50% -60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL) for Azure DP-900 exam preparation.
  • Microsoft certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.
  • Being a Microsoft Learning Partner provides us with the edge over competition.

Who Should Attend

  • Azure Database Administrator
  • Azure Data Engineer

Prerequisites

  • Should have knowledge on concepts of relational and non-relational data
  • Should have knowledge on different types of data workloads such as transactional or analytical

Course Outline Download Course Outline

Describe Types of Core Data Workloads

  • Describe Batch Data
  • Describe Streaming Data
  • Describe the Difference between Batch and Streaming Data
  • Describe the Characteristics of Relational Data

Describe Data Analytics Core Concepts

  • Describe Data Visualization (e.g., Visualization, Reporting, Business Intelligence
  • Describe Basic Chart Types such as Bar Charts and Pie Charts
  • Describe Analytics Techniques (e.g., Descriptive, Diagnostic, Predictive, Prescriptive, Cognitive)
  • Describe ELT and ETL Processing
  • Describe the Concepts of Data Processing

Describe Relational Data Workloads

  • Identify the right Data Offering for a Relational Workload
  • Describe Relational Data Structures (e.g., tables, index, views)

Describe Relational Azure Data Services

  • Describe and compare PaaS, IaaS, and SaaS Delivery Models
  • Describe Azure SQL Database
  • Describe Azure Synapse Analytics
  • Describe SQL Server on Azure Virtual Machine
  • Describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure

Database for MySQL

  • Describe Azure SQL Managed Instance

Identify Basic Management Tasks for Relational Data

  • Describe Provisioning and Deployment of Relational Data Services
  • Describe Method for Deployment Including ARM Templates and Azure Portal
  • Identify Data Security Components (e.g., Firewall, Authentication)
  • Identify Basic Connectivity Issues (e.g., Accessing from On-premises, Access with Azure

VNets, Access from Internet, Authentication, Firewalls)

  • Identify Query Tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd Utility, etc.)

Describe Query Techniques for Data using SQL Language

  • Compare DDL Versus DML
  • query relational Data in PostgreSQL, MySQL, and Azure SQL Database

Describe Non-Relational Data Workloads

  • Describe the Characteristics of Non-Relational Data
  • Describe the Types of Non-Relational and NoSQL Data
  • Recommend the Correct Data Store
  • Determine When to use Non-Relational Data

Describe non-relational Data Offerings on Azure

  • Identify Azure Data Services for Non-Relational Workloads
  • Describe Azure Cosmos DB APIs
  • Describe Azure Table Storage
  • Describe Azure Blob Storage
  • Describe Azure File Storage

Identify Basic Management Tasks for Non-Relational Data

  • Describe Provisioning and Deployment of Non-Relational Data Services
  • Describe Method for Deployment Including ARM Templates and Azure Portal
  • Identify Data security components (e.g., Firewall, Authentication)
  • Identify Basic Connectivity Issues (e.g., Accessing from On-Premises, Access with Azure VNets, Access from Internet, Authentication, Firewalls)
  • Identify Management Tools for Non-Relational Data

Describe Analytics Workloads

  • Describe Transactional Workloads
  • Describe the Difference Between a Transactional and an Analytics Workload
  • Describe the Difference between Batch and Real Time
  • Describe Data Warehousing Workloads
  • Determine when a Data Warehouse Solution is Needed

Describe the components of a Modern Data Warehouse

  • Describe Azure Data Services for Modern Data Warehousing such as Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight
  • Describe Modern Data Warehousing Architecture and Workload

Describe Data Ingestion and Processing on Azure

  • Describe Common Practices for Data Loading
  • Describe the Components of Azure Data Factory (e.g., Pipeline, Activities, etc.)
  • Describe Data Processing Options (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)

Describe Data Visualization in Microsoft Power BI

  • Describe the Role of paginated Reporting
  • Describe the Role of Interactive Reports
  • Describe the Role of Dashboards
  • Describe the Workflow in Power BI

Certification

    • By earning Microsoft DP-900 certification, you will prove competency to work with data deployed on cloud.
    • Imbibe skills to build AI solutions on Azure.
    • Demonstrate abilities to Azure Machine Learning services usage & integration.
    • On successful completion of DP-900: Microsoft Azure Data Fundamentals training aspirants receive a Course Completion Certificate from us.
    • By successfully clearing the DP-900: Microsoft Azure Data Fundamentals exams, aspirants earn Microsoft Certification.

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