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Real Microsoft 70-773 practice exam questions for easy pass!

Updated: Sep 09, 2026

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

itPass4sure 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
  • DataSets
  • Data Processing with RxDataStep
  • Spark
  • Work Flow Analysis
  • Read Data with R Server
  • Transform Functions
  • Linear Model, Partitioning Models

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

Microsoft 70-773 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Analyzing Big Data with Microsoft R
Exam Number:70-773
Real Exam Qty:40-60
Exam Duration:120 minutes
Certificate Validity Period:Certification retired (Exam retired June 30, 2019)
Passing Score:700/1000
Exam Price:USD 165
Related Certifications:MCSA: Machine Learning
Available Languages:English
Exam Format:Multiple Response, Scenario-based Questions, Case Study, Multiple Choice
Sample Questions:Microsoft 70-773 Sample Questions
Exam Way:Pearson VUE testing center or online proctored delivery (before retirement).
Pre Condition:No mandatory prerequisite exam. This exam was one of the required exams for the MCSA: Machine Learning certification path.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/posts/mapping-microsoft-70-xxx-exams-to-new-role-based-certifications

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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Microsoft 70-773 Exam Syllabus Topics:

SectionObjectives
Topic 1: Read and Explore Big Data- Read data with R Server
- Visualize data
- Summarize data
Topic 2: Use R Server in Different Environments- Use different compute contexts to run R Server effectively
- Perform in-database analytics using SQL Server
- Deploy predictive models to SQL Server and Azure Machine Learning
- Implement analysis workflows in Hadoop and Spark
- Optimize tasks using local compute contexts
Topic 3: Process Big Data- Process data with rxDataStep
- Perform complex transforms using transform functions
- Process text using MicrosoftML packages
- Manage data sets
Topic 4: Build Predictive Models with ScaleR- Generate predictions and residuals
- Create additional models using MicrosoftML packages
- Evaluate models and tuning parameters
- Build and use partitioning models
- Estimate linear models

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