Data Engineering on Microsoft Azure | DP-203 | DP203
"Goede trainer die met veel inzet heeft geprobeerde alle falende onderdelen van de cursus probeerde recht te breien. De cursus past met de labs absoluut niet in 4 dagen, kies een opleider die minimaal 5 dagen de tijd neemt om de stof van DP-203 goed door te nemen. In deze training moesten veel theorie presentaties worden afgeraffeld en konden alleen ervaren Azure/Synapse gebruiker alles afronden." - 05-07-2021 08:38
"Goede trainer die met veel inzet heeft geprobeerde alle falende onderdelen van de cursus probeerde recht te breien. De cursus past met de la… read full review - 05-07-2021 08:38
Starting dates and places
placeAmsterdam 29 Apr 2024 until 2 May 2024 |
computer Online: Dynamic Virtual Classroom 29 Apr 2024 until 2 May 2024 |
computer Online: Dynamic Virtual Classroom - Engels 27 May 2024 until 30 May 2024 |
placeNieuwegein Engels 27 May 2024 until 30 May 2024 |
computer Online: Dynamic Virtual Classroom 24 Jun 2024 until 27 Jun 2024 |
placeNieuwegein 24 Jun 2024 until 27 Jun 2024 |
computer Online: Dynamic Virtual Classroom - Engels 29 Jul 2024 until 1 Aug 2024 |
computer Online: Dynamic Virtual Classroom 26 Aug 2024 until 29 Aug 2024 |
placeNieuwegein 26 Aug 2024 until 29 Aug 2024 |
computer Online: Dynamic Virtual Classroom - Engels 23 Sep 2024 until 26 Sep 2024 |
placeNieuwegein Engels 23 Sep 2024 until 26 Sep 2024 |
computer Online: Dynamic Virtual Classroom 28 Oct 2024 until 31 Oct 2024 |
placeAmsterdam - Engels 25 Nov 2024 until 28 Nov 2024 |
computer Online: Dynamic Virtual Classroom - Engels 25 Nov 2024 until 28 Nov 2024 |
computer Online: Dynamic Virtual Classroom 16 Dec 2024 until 19 Dec 2024 |
placeNieuwegein 16 Dec 2024 until 19 Dec 2024 |
Description
Data Engineering on Microsoft Azure | DP-203
In this course, the student 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. Students 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 students 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…
Frequently asked questions
There are no frequently asked questions yet. If you have any more questions or need help, contact our customer service.
Data Engineering on Microsoft Azure | DP-203
In this course, the student 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. Students 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 students 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 students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student 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 student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics.
Doelstellingen
– 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 Synpase
Analytics
– Perform Integrated Machine Learning Processes in Azure Synapse
Analytics
Voorkennis
Successful students start this course with knowledge of cloud
computing and core data concepts and professional experience with
data solutions.
– Microsoft Azure Fundamentals | AZ-900
– Microsoft Azure Data Fundamentals | DP-900
Voor wie
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.
Inhoud
– 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
Synpase Analytics
– Module 17: Perform Integrated Machine Learning Processes in Azure
Synapse Analytics
Exclusief examen
DP-203 Data engineering on Microsoft Azure
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Duur
4 dagen
Meer informatie
Kijk op onze website voor gedetailleerde lesinhoud, examens en meer details van deze training.
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"Goede trainer die met veel inzet heeft geprobeerde alle falende onderdelen van de cursus probeerde recht te breien. De cursus past met de labs absoluut niet in 4 dagen, kies een opleider die minimaal 5 dagen de tijd neemt om de stof van DP-203 goed door te nemen. In deze training moesten veel theorie presentaties worden afgeraffeld en konden alleen ervaren Azure/Synapse gebruiker alles afronden." - 05-07-2021 08:38
"Goede trainer die met veel inzet heeft geprobeerde alle falende onderdelen van de cursus probeerde recht te breien. De cursus past met de la… read full review - 05-07-2021 08:38
There are no frequently asked questions yet. If you have any more questions or need help, contact our customer service.