Microsoft Analyzing Big Data with Microsoft R : 070-773

  • Exam Code: 070-773
  • Exam Name: Analyzing Big Data with Microsoft R
  • Updated: Jul 30, 2026
  • Q&As: 40 Questions and Answers

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Benefits of having MICROSOFT 70-773 Certifications

MICROSOFT 70-773 Exam certification will not only help you learn some new skills, it can position you for a higher paying job or help you transform your current role into a Big Data and Analytics professional. Get prepared to take this exam and become one of the very first Microsoft Big Data Certified professionals in the world using our relevance quality of MICROSOFT 70-773 Exam study material and so we bring best-in-industry MICROSOFT 70-773 Exam online course and practice exams for you to help in your exam preparation.

Difficulty in writing MICROSOFT 70-773 Exam

It is one of the toughest exam and it requires you a lot of hands-on experience. It is advisable to have prior knowledge of Big Data technologies on Microsoft. The more experience you have, the more it is beneficial for you, Major challenging things which you can find in exam is about different scenario based questions, you must have strong understanding of Big Data.

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Reference: https://www.microsoft.com/en-us/learning/exam-70-773.aspx

Steps for MICROSOFT 70-773 Certifications Exam booking

  • Visit to Microsoft Exam Registration
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Analyzing Big Data with Microsoft R 70-773 Dumps will include below mentioned topics with Exam focused percentage

  • Build predictive models with Scale R: 20-25%
  • Process big data: 20-25%
  • Use R Server in different environments: 20-25%
  • Implement Domain Name System (DNS): 15-20%
  • Read and explore big data: 20-25%

Microsoft 070-773 Exam Syllabus Topics:

SectionWeightObjectives
Evaluate and Optimize Models20%- Optimize R scripts for scale and speed
- Tune model parameters
- Assess model performance
Deploy and Operationalize R Solutions15%- Manage scalable analytics workflows
- Integrate R with SQL Server R Services
- Run R scripts in Hadoop/Spark environments
Manage Data Sets20%- Transform and clean data
- Handle large datasets beyond memory
- Read and write data using Microsoft R Server
Explore and Visualize Data20%- Perform exploratory data analysis
- Create visualizations using R and RevoScaleR
- Summarize and aggregate data
Build Statistical and Machine Learning Models25%- Use partitioning and parallelized models
- Train linear and generalized linear models
- Process text data with RML packages

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