Microsoft Analyzing Big Data with Microsoft R : 070-773 Exam

  • Exam Code: 070-773
  • Exam Name: Analyzing Big Data with Microsoft R
  • Updated: Aug 07, 2026
  • Q & A: 40 Questions and Answers

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About Microsoft Analyzing Big Data with Microsoft R : 070-773 Exam Questions

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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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Overview about MICROSOFT 70-773 Exam

  • Length of Examination: 150 minutes
  • Format: Multiple choice, multiple answer
  • Passing Score: 70-80%
  • Registration Fee: 165 USD
  • Number of Questions: 40-60

Analyzing Big Data with Microsoft R 70-773 Dumps Provided Study Notes

DumpsActual expert team recommend you to prepare some notes on these topics along with it don't forget to practice Analyzing Big Data with Microsoft R 70-773 Dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.

  • Hadoop
  • Work Flow Analysis
  • Linear Model, Partitioning Models
  • Spark
  • Read Data with R Server
  • Data Processing with RxDataStep
  • DataSets
  • Transform Functions

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

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

  • Read and explore big data: 20-25%
  • 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%

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Microsoft 070-773 Exam Syllabus Topics:

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

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