Description
Candidates for this examination ought to have foundational data of core knowledge ideas and the way they’re applied utilizing Microsoft Azure knowledge companies.
This examination is meant for candidates starting to work with knowledge within the cloud.
Candidates must be accustomed to the ideas of relational and non-relational knowledge, and several types of knowledge workloads equivalent to transactional or analytical.
Azure Data Fundamentals can be utilized to organize for different Azure role-based certifications like Azure Database Administrator Affiliate or Azure Data Engineer Affiliate, but it surely’s not a prerequisite for any of them.
Abilities Measured
Describe core knowledge ideas (15-20%)
Describe kinds of core knowledge workloads · describe batch knowledge · describe streaming knowledge · describe the distinction between batch and streaming knowledge · describe the traits of relational knowledge Describe knowledge analytics core ideas · describe knowledge visualization (e.g., visualization, reporting, enterprise intelligence · describe fundamental chart sorts equivalent to bar charts and pie charts · describe analytics strategies (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive) · describe ELT and ETL processing · describe the ideas of information processing
Describe how one can work with relational knowledge on Azure (25-30%)
Describe relational knowledge workloads · establish the precise knowledge providing for a relational workload · describe relational knowledge constructions (e.g., tables, index, views) Describe relational Azure knowledge companies · describe and evaluate PaaS, IaaS, and SaaS supply fashions · describe Azure SQL Database · describe Azure Synapse Analytics · describe SQL Server on Azure Digital Machine · describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL · describe Azure SQL Managed Occasion Determine fundamental administration duties for relational knowledge · describe provisioning and deployment of relational knowledge companies · describe technique for deployment together with ARM templates and Azure Portal · establish knowledge safety parts (e.g., firewall, authentication) · establish fundamental connectivity points (e.g., accessing from on-premises, entry with Azure VNets, entry from Web, authentication, firewalls) · establish question instruments (e.g., Azure Data Studio, SQL Server Administration Studio, sqlcmd utility, and so on.) Describe question strategies for knowledge utilizing SQL language · evaluate DDL versus DML · question relational knowledge in PostgreSQL, MySQL, and Azure SQL Database
Describe how one can work with non-relational knowledge on Azure (25-30%)
Describe non-relational knowledge workloads · describe the traits of non-relational knowledge · describe the kinds of non-relational and NoSQL knowledge · advocate the proper knowledge retailer · decide when to make use of non-relational knowledge Describe non-relational knowledge choices on Azure · establish Azure knowledge companies for non-relational workloads · describe Azure Cosmos DB APIs · describe Azure Desk storage · describe Azure Blob storage · describe Azure File storage Determine fundamental administration duties for non-relational knowledge · describe provisioning and deployment of non-relational knowledge companies · describe technique for deployment together with ARM templates and Azure Portal · establish knowledge safety parts (e.g., firewall, authentication) · establish fundamental connectivity points (e.g., accessing from on-premises, entry with Azure VNets, entry from Web, authentication, firewalls) · establish administration instruments for non-relational knowledge
Describe an analytics workload on Azure (25-30%)
Describe analytics workloads · describe transactional workloads · describe the distinction between a transactional and an analytics workload · describe the distinction between batch and actual time · describe knowledge warehousing workloads · decide when a knowledge warehouse resolution is required Describe the parts of a contemporary knowledge warehouse · describe Azure knowledge companies for contemporary knowledge warehousing equivalent to Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight · describe trendy knowledge warehousing structure and workload Describe knowledge ingestion and processing on Azure · describe frequent practices for knowledge loading · describe the parts of Azure Data Manufacturing facility (e.g., pipeline, actions, and so on.) · describe knowledge processing choices (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Manufacturing facility) Describe knowledge visualization in Microsoft Energy BI · describe the function of paginated reporting · describe the function of interactive reviews · describe the function of dashboards · describe the workflow in Energy BI
If the coupon is just not opening, disable Adblock, or strive one other browser.