This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.
oferecido por
Data Processing with Azure
LearnQuestInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Francês, Portuguese (European), Russo, Inglês, Espanhol
O que você vai aprender
Configure batch processing with Databricks and Data Factory on Azure
Use ETL and ELT to load and transform data
Create linked services and identify pipelines for data stored within Data Factory
Explain Data Virtualization in PolyBase
Habilidades que você terá
- Data Analysis
- Microsoft Azure
- Big Data
- Data Lake
- Data Factory
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Francês, Portuguese (European), Russo, Inglês, Espanhol
oferecido por
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Programa - O que você aprenderá com este curso
7 minutos para concluir
Introduction
This Azure training course is designed to equip the students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as R, and Apache Spark.
7 minutos para concluir
1 vídeo (Total 7 mín.)
2 horas para concluir
Section 1 - Batch Processing with Databricks and Data Factory on Azure
One of the primary benefits of Azure Databricks is its ability to integrate with many other data environments to pull data through an ETL or ELT process. In module course, we examine each of the E, L, and T to learn how Azure Databricks can help ease us into a cloud solution.
2 horas para concluir
5 vídeos (Total 40 mín.), 3 leituras, 1 teste
2 horas para concluir
Section 2 - Creating Pipelines and Activities
Processing big data in real-time is now an operational necessity for many businesses. Azure Stream Analytics is Microsoft’s serverless real-time analytics offering for complex event processing. In this section we examine how customers unlock valuable insights and gain competitive advantage by harnessing the power of big data.
2 horas para concluir
4 vídeos (Total 46 mín.), 3 leituras, 1 teste
2 horas para concluir
Section 3 - Link Services and Datasets
A data factory can have one or more pipelines. A pipeline is a logical grouping of activities that together perform a task. The activities in a pipeline define actions to perform on your data. Before you create a dataset, you must create a linked service to link your data store to the data factory. This section deals with linked services and data sets within Azure Blob Storage.
2 horas para concluir
5 vídeos (Total 38 mín.), 1 leitura, 1 teste
1 hora para concluir
Section 4 - Schedules and Triggers
Azure Data Factory is a fully managed, cloud-based data orchestration service that enables data movement and transformation. In this section, we explore scheduling triggers for Azure Data Factory to automate your pipeline execution.
1 hora para concluir
5 vídeos (Total 17 mín.), 1 leitura, 1 teste
2 horas para concluir
Section 5 - Selecting Windowing Functions
In time-streaming scenarios, performing operations on the data contained in temporal windows is a common pattern. Stream Analytics has native support for windowing functions, enabling developers to author complex stream processing jobs with minimal effort. In this section, we study windowing functions related to in-stream analytics.
2 horas para concluir
5 vídeos (Total 30 mín.), 1 leitura, 1 teste
2 horas para concluir
Section 6 - Configuring Input and Output for Streaming Data Solutions
This section teaches how to analyze phone call data using Azure Stream Analytics. The phone call data, generated by a client application, contains some fraudulent calls, which will be filtered by the Stream Analytics job.
2 horas para concluir
7 vídeos (Total 33 mín.), 1 leitura, 1 teste
1 hora para concluir
Section 7 - ELT versus ETL in Polybase
Traditional SMP data warehouses use an Extract, Transform and Load (ETL) process for loading data. Azure SQL Data Warehouse is a massively parallel processing (MPP) architecture that takes advantage of the scalability and flexibility of compute and storage resources. Utilizing an Extract, Load, and Transform (ELT) process can take advantage of MPP and eliminate resources needed to transform the data prior to loading.
1 hora para concluir
4 vídeos (Total 21 mín.), 1 leitura, 1 teste
Avaliações
Principais avaliações do DATA PROCESSING WITH AZURE
por JM28 de Abr de 2021
This course gave a detailed overview of Microsoft azure,
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