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Performing Big Data Engineering on Microsoft Cloud Services - Moc On Demand (MS-20776)

Let’s have an insight on what big data is. The term big data is used for a significant amount of data (both unstructured and structured) that inundates a company on a day to day basis. However, the volume of data is not the only thing that matters.


Self-Paced

Learning Style

Microsoft

Provider

Intermediate

Difficulty

2 Days

Course Duration

2

SATV Value

Course Info

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Let’s have an insight on what big data is. The term big data is used for a significant amount of data (both unstructured and structured) that inundates a company on a day to day basis. However, the volume of data is not the only thing that matters.

Course Information

About this course:                                         

Let’s have an insight on what big data is. The term big data is used for a significant amount of data (both unstructured and structured) that inundates a company on a day to day basis. However, the volume of data is not the only thing that matters. The important thing is that what businesses do with the data. Big data can be examined for insights that lead to better strategic business moves and decisions. This program enables the candidate to process big data utilizing MS Azure services and tools including MS Azure Data Lake, MS Azure Data Factory, MS Azure Stream Analytics, and MS Azure SQL Data Warehouse. This course also describes how to incorporate custom functions, and integrate R and Python.

Salary Estimate:

Big Data Engineer can earn an average salary of $90,286 per annum. 

 

Course Objective: 

After successful completion of this course, candidates are able to:

  • Explain the method to include machine learning activities and incorporate custom functions into an MS Azure Stream Analytics job.
  • Define general architectures for processing big data utilizing MS Azure services and tools.
  • Define how to deploy and create custom operations and functions, optimize and protect, and jobs integrate with R and Python.
  • Guidance to utilize MS Azure SQL Data Warehouse to execute analytical processing, how to secure the data, and how to maintain performance.
  • Provide instruction to utilize MS Azure Data Factory to transform, import, and transfer data between services and repositories.
  • How MS Azure Stream Analytics is used to implement and design stream processing over large-scale data.
  • Provide instruction to utilize MS Azure Data Lake Analytics to process and examine data held in MS Azure Data Lake Store.
  • Define the way to utilize MS Azure Data Lake Store as a large-scale repository of data files.

 

Audience: 

This course is designed for: 

  • Data engineers (Information workers, Developers, and IT professionals) 

 

Prerequisites:

  • A fundamental understanding of the Microsoft Windows OS and its main functions.
  • Understanding of relational databases.
  • A sound knowledge of MS Azure data services.

Outline

More Information

More Information
Brand Microsoft
Subjects Big Data, Cloud Computing
Lab Access No
Technology Microsoft, MOCOD
Learning Style Self-Paced Learning
Learning Type Course
Difficulty Intermediate
Course Duration 2 Days
Language English
SATV Value 2
VPA Discount VPA Discount

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