Data Engineering on Microsoft Azure (DP-203) Opslaan als favoriet Deel deze pagina Printen Duur 4 dagen Prijs € 2495,- 8,9 Reviews 1000+ reviews Locatie Nieuwegeinvirtueel Planning Planning ophalen... Lesvorm klassikaal Schrijf je direct in Meer informatie Brochure downloaden We offer you a free Microsoft exam voucher. In this course, the candidate will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Candidates will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The candidates will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The candidates will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The candidate will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The candidate will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. Doel Rampup in order to pass for the exam DP-203: Data Engineering on Microsoft Azure. When you pass for this exam you obtain the Microsoft Role-Based Microsoft Certified: Azure Data Engineer Associate certificate. After completing this course, students will be able to: Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synapase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics Doelgroep The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure. Voorkennis Microsoft Azure Fundamentals (AZ-900) of vergelijkbare kennis.Microsoft Azure Data Fundamentals (DP-900) of vergelijkbare kennis.For this course (and the related exam) you should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions. In addition to their professional experience, candidates who take this course should have technical knowledge equivalent to the DP-900 Microsoft Azure Data Fundamentals course. Persoonlijk advies? Lucas Ditvoorst key accountmanager T. 088 542 78 53 E. l.ditvoorst@vijfhart.nl Onderwerpen Module 1: Explore compute and storage options for data engineering workloads Module 2: Design and implement the serving layer Module 3: Data engineering considerations for source files Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Module 6: Data exploration and transformation in Azure Databricks Module 7: Ingest and load data into the data warehouse Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse Module 11: Analyze and Optimize Data Warehouse Storage Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Module 13: End-to-end security with Azure Synapse Analytics Module 14: Real-time Stream Processing with Stream Analytics Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Module 16: Build reports using Power BI integration with Azure Synapase Analytics Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Bekijk meer onderwerpenBekijk minder onderwerpen Module 1: Explore compute and storage options for data engineering workloads Introduction to Azure Synapse Analytics Describe Azure Databricks Introduction to Azure Data Lake storage Describe Delta Lake architecture Work with data streams by using Azure Stream Analytics Module 2: Design and implement the serving layer Design a multidimensional schema to optimize analytical workloads Code-free transformation at scale with Azure Data Factory Populate slowly changing dimensions in Azure Synapse Analytics pipelines Module 3: Data engineering considerations for source files Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools Explore Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Understand big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Module 6: Data exploration and transformation in Azure Databricks Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Module 7: Ingest and load data into the data warehouse Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines Data integration with Azure Data Factory or Azure Synapse Pipelines Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Module 11: Analyze and Optimize Data Warehouse Storage Analyze and optimize data warehouse storage in Azure Synapse Analytics#Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark pools Query Azure Cosmos DB with serverless SQL pools Module 13: End-to-end security with Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Module 14: Real-time Stream Processing with Stream Analytics Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Process streaming data with Azure Databricks structured streaming Module 16: Build reports using Power BI integration with Azure Synapase Analytics Create reports with Power BI using its integration with Azure Synapse Analytics Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Use the integrated machine learning process in Azure Synapse Analytics Planning & Prijs * *Een cursus met start gegarandeerd. *Een cursus met valt onder de actie Summer Academy. Alle prijzen zijn excl. BTW. Meer informatie over incompany of maatwerk Cursus: Data Engineering on Microsoft Azure (DP-203) Vul onderstaand formulier in en je ontvangt meer informatie over de incompany- en maatwerkmogelijkheden van deze cursus. [contact-form-7 404 "Niet gevonden"] Wil je meer informatie ontvangen, een vrijblijvende offerte ontvangen of een brochure van deze cursus downloaden? Vul onderstaande gegevens in en je ontvangt de brochure of informatie binnen één werkdag. Offerte aanvragen Brochure downloaden Informatie aanvragen Soort training Deze cursus op eigen locatieEen maatwerk oplossing Akkoord met opvolging en privacyvoorwaardenIk ga akkoord met de privacy voorwaarden Akkoord met opvolging en privacyvoorwaardenIk ga akkoord met de privacy voorwaarden Akkoord met opvolging en privacyvoorwaardenIk ga akkoord met de privacy voorwaarden Gerelateerde cursussen Werken met Microsoft 365 Copilot Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Fundamentals (AZ-900) – Intensief Microsoft Security, Compliance and Identity Fundamentals (SC-900) Microsoft Azure AI Fundamentals (AI-900) Microsoft Azure Data Fundamentals (DP-900) Administering Windows Server Hybrid Core Infrastructure (AZ-800) Automating Administration With PowerShell (AZ-040) Configuring and Operating Azure Virtual Desktop (AZ-140) Configuring Windows Server Hybrid Advanced Services (AZ-801) Vervolgcursussen Designing and Implementing a Data Science Solution on Azure (DP-100) Ervaringen ervaringen verzameld via Lucienne Groenendaal Secretarieel medewerkster "Training was prima, goede tips gekregen met af en toe een grap en grol. Locatie was prima, goed verzogd vwb koffie/thee, fruit en koekje. Mensen ook zeer vriendelijk. Lunch was perfect en zeer uitgebreid." 9 Ariana Scheepers "De cursus was goed, en de verzorging ook!Ik heb er veel van opgestoken! De lokatie in Nieuwegein is goed te bereiken met het openbaar vervoer, dus dat is prettig. Tot een volgenden keer." 10 Eric Pos Procesbeheerder bij Gemeente Amersfoort "Ik vond de training erg leerzaam. De inhoud was van een hoog niveau en de docent was goed thuis in de materie. Ik stel het vooral op prijs dat er diep op de concepten werd ingegaan." 9 Tags: MicrosoftDataArtificial IntelligenceBig DataMachine LearningMicrosoft development & beheerVirtuele training Share: Share Share Share Share
Lucienne Groenendaal Secretarieel medewerkster "Training was prima, goede tips gekregen met af en toe een grap en grol. Locatie was prima, goed verzogd vwb koffie/thee, fruit en koekje. Mensen ook zeer vriendelijk. Lunch was perfect en zeer uitgebreid." 9
Ariana Scheepers "De cursus was goed, en de verzorging ook!Ik heb er veel van opgestoken! De lokatie in Nieuwegein is goed te bereiken met het openbaar vervoer, dus dat is prettig. Tot een volgenden keer." 10
Eric Pos Procesbeheerder bij Gemeente Amersfoort "Ik vond de training erg leerzaam. De inhoud was van een hoog niveau en de docent was goed thuis in de materie. Ik stel het vooral op prijs dat er diep op de concepten werd ingegaan." 9