Wij slaan cookies op om onze website te verbeteren. Is dat akkoord? Ja Nee Meer over cookies »

Examen DP-900 Microsoft Azure Data Fundamentals

Examen DP-900 Microsoft Azure Data Fundamentals

145,00 175,45 Incl. btw

Beheerst u Microsoft Azure Data Fundamentals DP-900 ? Bestel online en maak een afspraak voor het Microsoft Azure Data Fundamentals DP-900

Lees meer
Beschikbaarheid:
Op voorraad
Levertijd:
Examendatum & tijd op afspraak
  • Award Winning E-learning
  • De laagste prijs garantie
  • Persoonlijke service van ons deskundige team
  • Betaal veilig online of op factuur
  • Bestel en start binnen 24 uur

Examen DP-900 Microsoft Azure Data Fundamentals

Dit examen is bedoeld voor kandidaten die beginnen te werken met data in de cloud.

Kandidaten voor dit examen moeten een basiskennis hebben van de belangrijkste data-concepten en hoe deze worden geïmplementeerd met behulp van Microsoft Azure data services, en moeten bekend zijn met de concepten van relationele en niet-relationele data, en verschillende soorten data workloads zoals transactionele of analytische.

Skills measured

Audience profile

This exam is an opportunity to demonstrate your knowledge of core data concepts and related Microsoft Azure data services. As a candidate for this exam, you should have familiarity with Exam DP-900’s self-paced or instructor-led learning material.

This exam is intended for you, if you’re a candidate beginning to work with data in the cloud.

You should be familiar with:

  • The concepts of relational and non-relational data.

  • Different types of data workloads such as transactional or analytical.

You can use Azure Data Fundamentals to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.

Skills at a glance

  • Describe core data concepts (25–30%)

  • Identify considerations for relational data on Azure (20–25%)

  • Describe considerations for working with non-relational data on Azure (15–20%)

  • Describe an analytics workload on Azure (25–30%)

Describe core data concepts (25–30%)

Describe ways to represent data

  • Describe features of structured data

  • Describe features of semi-structured

  • Describe features of unstructured data

Identify options for data storage

  • Describe common formats for data files

  • Describe types of databases

Describe common data workloads

  • Describe features of transactional workloads

  • Describe features of analytical workloads

Identify roles and responsibilities for data workloads

  • Describe responsibilities for database administrators

  • Describe responsibilities for data engineers

  • Describe responsibilities for data analysts

Identify considerations for relational data on Azure (20–25%)

Describe relational concepts

  • Identify features of relational data

  • Describe normalization and why it is used

  • Identify common structured query language (SQL) statements

  • Identify common database objects

Describe relational Azure data services

  • Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines

  • Identify Azure database services for open-source database systems

Describe considerations for working with non-relational data on Azure (15–20%)

Describe capabilities of Azure storage

  • Describe Azure Blob storage

  • Describe Azure File storage

  • Describe Azure Table storage

Describe capabilities and features of Azure Cosmos DB

  • Identify use cases for Azure Cosmos DB

  • Describe Azure Cosmos DB APIs

Describe an analytics workload on Azure (25–30%)

Describe common elements of large-scale analytics

  • Describe considerations for data ingestion and processing

  • Describe options for analytical data stores

  • Describe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, Azure HDInsight, and Azure Data Factory

Describe consideration for real-time data analytics

  • Describe the difference between batch and streaming data

  • Identify Microsoft cloud services for real-time analytics

Describe data visualization in Microsoft Power BI

  • Identify capabilities of Power BI

  • Describe features of data models in Power BI

  • Identify appropriate visualizations for data

 

Duur 50 minuten
Locatie Almere
Taal Engels
Parkeren Gratis

Er zijn nog geen reviews geschreven over dit product.

Loading...

OEM Office Elearning Menu Trots Genomineerd voor 'Beste Opleider van Nederland'

OEM Office Elearning Menu is vereerd met de nominatie voor 'Beste Opleider van Nederland' door Springest by STUDYTUBE, een blijk van erkenning voor onze excellente trainingen en toewijding aan kwaliteitsonderwijs. Dank aan alle cursisten.

Beoordelingen

Er zijn nog geen reviews geschreven over dit product.

25.000+

Deelnemers getrained

Springest: 9.1 - Edubookers 8.9

Gemiddeld cijfer

3500+

Aantal getrainde bedrijven

20+

Jaren ervaring

Nóg meer kennis

Lees onze meest recente blogartikelen

Bekijk alles