DP-900 Azure Data Fundamentals hands on course with sims

DP-900 Azure Data Fundamentals hands on course with sims free download

Get prepared for the DP-900 exam with instructor led labs and hands on simulations available 24/7

We really hope you'll agree, this training is way more than the average course on Udemy!

Have access to the following:

• Training from an instructor of over 25 years who has trained thousands of people and also a Microsoft Certified Trainer

• Lecture that explains the concepts in an easy to learn method for someone that is just starting out with this material

• Instructor led hands on and simulations to practice that can be followed even if you have little to no experience

TOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:

Introduction

• Welcome to the course

• Understanding the Microsoft Environment

• Having a Solid Foundation of Active Directory Domains

• Having a Solid Foundation of RAS, DMZ, and Virtualization

• Having a Solid Foundation of the Microsoft Cloud Services

• Order of concepts covered in the course

Setting up for hands on

• IMPORTANT Using Assignments in the course

• Creating a free Azure Account

• Activating Entra ID P2 license

Describe ways to represent data

• Features of structured data

• Features of semi-structured

• Features of unstructured data

Identify options for data storage

• Understanding formats for data files

• Relational databases as a type of data storage

• Creating a relational database in Azure using Microsoft SQL

• Installing SQL Server Management Studio (SSMS) for connecting to SQL

• Connecting to a SQL database with SSMS

• Non-relational databases as a type of data storage

• Creating a non-relational database in Azure using Microsoft Cosmos

• Connecting to a Microsoft Cosmos database

Describe common data workloads

• Features of transactional workloads

• Features of analytical workloads

Identify roles and responsibilities for data workloads

• Responsibilities for database administrators

• Permissions in Azure regarding a database administrator

• Responsibilities for data engineers

• Permissions in Azure regarding a data engineers

• Responsibilities for data analysts

• Permissions regarding a data analysts

Describe relational concepts

• Features of relational data

• Normalization and why it is used

• Creating an Azure VM with Microsoft SQL server

• Using common structured query language (SQL) statements

• A look at common database objects

Describe relational Azure data services

• Azure SQL Family: Azure SQL Database, SQL Managed Instance, SQL Server on VMs

• Azure database services for open-source database systems

Describe capabilities of Azure storage

• Understanding the capabilities of Azure storage accounts

• Creating a storage account to explore Blob, File, & Table storage capabilities

• Securing a Azure storage account

• Utilizing Azure Blob storage

• Utilizing Azure File storage

• Utilizing Azure Table storage

Describe capabilities and features of Azure Cosmos DB

• Use cases for Azure Cosmos DB

• Understanding the Azure Cosmos DB APIs

• Deleting the existing Cosmos DB before moving on

• Creating a new Cosmos DB account for NoSQL

• Adding and querying data within a Cosmos DB for NoSQL

• Cleaning up our lab environment to this point

Describe common elements of large-scale analytics

• Considerations for data ingestion and processing

• Understanding Azure Data Lake storage

• Creating an Azure Data Lake storage account

• Understanding Azure Databricks

• Visualizing Azure Synapse Analytics

• Registering Azure Synapse as a resource provider in Azure

• Setting up a SQL DB and server for use with Azure Synapse Analytics

• Creating a Azure Synapse workspace and Data Lake Storage account

• Concepts of SQL Pool usage with Azure Synapse Analytics

• Purposes of Azure HDInsight

• Understanding Azure Data Factory

• Setting up an Azure Data Factory resources

• Using Azure Data Factory to copy data into Azure Synapse Analytics <AZ-305>

Describe consideration for real-time data analytics

• Understanding the difference between batch and streaming data

• Concepts of Azure Stream Analytics

• Creating an Azure Stream Analytics job for real-time analytics

• Benefits of using Apache Spark

• Cleaning up the existing resources before moving on

Describe data visualization in Microsoft Power BI

• Capabilities of Power BI

• Downloading and installing Power BI Desktop

• Creating a database with data for testing Power B

• Connecting Power BI to a SQL database and performing an import

• Features of data models in Power BI

• Using the appropriate visualizations for data