Microsoft Certified Azure Data Fundamentals Course in Dubai
Overview of Microsoft Certified Azure Data Fundamentals Course
Microsoft Certified Azure Data Fundamentals Course, candidates for the Azure Data Basics accreditation ought to have a foundational knowledge of core information principles as well as how they are applied utilizing Microsoft Azure data solutions. Zabeel Institute is considered as the best training institute in Dubai for Microsoft Certified Azure Data Fundamentals course.
This qualification is intended for candidates starting to work with data in the cloud.
Candidates ought to know with the ideas of relational and non-relational information, and various sorts of data work such as transactional or logical.
Azure Data Principles can be utilized to plan for various other Azure role-based accreditations like Azure Database Administrator Associate or Azure Data Designer Associate, yet it's not a requirement for any of them.
Job role: Database Administrator, Data Analyst, Data Engineer, Developer, Student
Required exams: DP-900
Microsoft Certified Azure Data Fundamentals Course Certification details
Exam DP-900: Microsoft Azure Data Fundamentals
Languages: English, Japanese, Chinese (Simplified), Korean, French, German, Spanish
Show that you can explain the following: core data ideas; how to deal with relational information on Azure; how to work with non-relational data on Azure; and also an analytics workload on Azure.
Candidates for this examination must have foundational knowledge of core data concepts and just how they are applied making use of Microsoft Azure data solutions.
This examination is meant for candidates starting to work with information in the cloud. Candidates ought to know with the concepts of relational and non-relational data, as well as various types of data work such as transactional or analytical. Azure Data Basics can be used to plan for various other Azure role-based certifications like Azure Data source Manager Affiliate or Azure Information Designer Affiliate, yet it's not a prerequisite for any of them.
Describe just how to deal with relational information on Azure
Define just how to work with non-relational data on Azure
Define an analytics workload on Azure
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explain the difference between batch and also streaming data
explain the characteristics of relational information
Describe data analytics core concepts
Explain information visualization (e.g., visualization, reporting, organization intelligence (BI)).
Define basic graph kinds such as bar charts and pie chart.
Explain analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, and cognitive).
Define ELT and ETL processing.
Describe the concepts of data handling.
Describe how to work with relational data on Azure (25-30%)
Describe relational data workloads
identify the appropriate data supplying for a relational workload
Explain relational data structures (e.g., tables, index, sights).
Describe relational Azure data services
Describe and contrast PaaS, IaaS, as well as SaaS services.
Define Azure SQL family members of items including Azure SQL Data source, Azure SQL Managed Circumstances, as well as SQL Server on Azure Virtual Machines.
Explain Azure Synapse Analytics.
Describe Azure Data source for PostgreSQL, Azure Database for MariaDB, and also Azure Database for MySQL.
Identify basic management tasks for relational data
Explain provisioning and deployment of relational data services.
describe technique for release including the Azure portal, Azure Source
Manager templates, Azure PowerShell, and also the Azure command-line interface (CLI).
Determine information safety and security components (e.g., firewall, verification).
Determine standard connectivity problems (e.g., accessing from on-premises, gain access to with Azure VNets, access from Web, verification, firewall softwares).
Identify inquiry tools (e.g., Azure Data Workshop, SQL Web Server Administration Workshop, sqlcmd utility, etc.).
Describe query techniques for data using SQL language
Contrast Data Definition Language (DDL) versus Information Control Language (DML).
Query relational information in Azure SQL Database, Azure Data Source for PostgreSQL, and also Azure Database for MySQL.
Describe how to work with non-relational data on Azure (25-30%)
Describe non-relational data workloads
describe the qualities of non-relational data
define the sorts of non-relational and also NoSQL data
recommend the proper information shop
establish when to use non-relational information
Describe non-relational data offerings on Azure
recognize Azure data services for non-relational workloads
define Azure Cosmos DB APIs
define Azure Table storage space
define Azure Blob storage space
explain Azure Data storage space
Identify basic management tasks for non-relational data
explain provisioning as well as implementation of non-relational information services
Define method for release including the Azure portal, Azure Resource Supervisor themes, Azure PowerShell, and the Azure command-line interface (CLI.
Recognize information security elements (e.g., firewall program, verification, and security).
Determine basic connection issues (e.g., accessing from on-premises, gain access to with Azure VNets, accessibility from Net, verification, firewall softwares).
Recognize management tools for non-relational information.
Describe an analytics workload on Azure (25-30%)
Describe analytics workloads
Explain transactional work.
Define the distinction in between a transactional and an analytics work.
Describe the difference between batch as well as actual time.
Explain information warehousing work.
Determine when an information warehouse option is required.
Describe the components of a modern data warehouse
Describe Azure information services for contemporary data warehousing such as Azure Data Lake Storage Space Gen2, Azure Synapse Analytics, Azure Data bricks, and Azure HDInsight.
Describe contemporary data warehousing design as well as workload.
Describe data ingestion and processing on Azure
Define usual methods for data filling.
Explain the elements of Azure Information Manufacturing facility (e.g., pipeline, activities, and so on).
Define information processing alternatives (e.g., Azure HDInsight, Azure Data bricks, Azure Synapse Analytics, Azure Data Factory).
