Microsoft 070-773 valid exam dumps : Analyzing Big Data with Microsoft R

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

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Microsoft 070-773 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Analyzing Big Data with Microsoft R
Exam Number:70-773
Real Exam Qty:40-60
Related Certifications:MCSA: Machine Learning
Exam Price:USD 165
Exam Format:Case Study, Multiple Response, Multiple Choice, Scenario-based Questions
Passing Score:700/1000
Certificate Validity Period:Certification retired (Exam retired June 30, 2019)
Exam Duration:120 minutes
Available Languages:English
Sample Questions:Free Download real 070-773 exam prep
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

Microsoft 070-773 Exam Syllabus Topics:

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

070-773 Exam FAQ: The Details That Matter

The Microsoft Analyzing Big Data with Microsoft R exam requires 700/1000 to pass, and registration costs USD 165. A failed attempt means paying the same fee again — a readiness check with the ValidDumps engines before booking is the cheaper option.

Microsoft recommends these training resources for the Microsoft Analyzing Big Data with Microsoft R exam:

    Follow the training with steady self-testing — the 40 practice questions from ValidDumps help you apply theory and fill any gaps the training leaves.

    The 070-773 exam is a Microsoft certification exam validating the Microsoft Analyzing Big Data with Microsoft R syllabus shown above. It belongs to these credential paths: MCSA: Machine Learning. Candidates in 2026 prepare for it with ValidDumps's 40 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.

    ValidDumps issues a full refund if you take the Microsoft Analyzing Big Data with Microsoft R exam within 60 days of purchase and do not pass. The policy does not apply if the exam is taken within 3 days of purchase, if the exam was never actually taken, or to free materials or expired orders, and the candidate name must match the payer name. Submit a scan of your enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, exchange for two free exam products of equal value and keep your original update service. Orders arrive by email within 1 minute — contact support if nothing arrives within 2 hours.

    Pearson VUE testing center or online proctored delivery (before retirement). Register for the Microsoft Analyzing Big Data with Microsoft R exam through these official channels:

      After booking, ValidDumps delivers your practice questions within 1 minute — preparation starts the same day.

      The Microsoft Analyzing Big Data with Microsoft R exam contains 40-60 to complete within 120 minutes. Timed simulation in the ValidDumps Desktop Test Engine teaches that rhythm before exam day does.

      The official Microsoft Analyzing Big Data with Microsoft R outline defines 4 domains. The leading three are Use R Server in Different Environments, Process Big Data, and Build Predictive Models with ScaleR. The full list is in the topics section above, and ValidDumps's 40 practice questions cover each one.

      Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows that simulates the real exam with two practice modes and works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 40 practice questions are identical across versions. Every purchase includes 365 days of free updates — whenever a new version is compiled, it is sent to you automatically — plus a 50% renewal discount afterward and unlimited computer installations.

      No mandatory prerequisite exam. This exam was one of the required exams for the MCSA: Machine Learning certification path. Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.

      Microsoft Analyzing Big Data with Microsoft R Sample Questions:

      Question #1

      You have cloud and on-premises resources that include Microsoft SQL Server and a big data environment in Apache Hadoop.
      You have 50 billion fact records.
      You need to build time series models to execute forecasting reports on the fact records.
      What should you use?

      • A. RxSpark on the Hadoop cluster
      • B. RxHadoopMR on the Hadoop cluster
      • C. RxLocalParallel on the SQL Server database
      • D. RxLocalseq on the SQL Server database
      Reveal Solution  Discussion  0

      Correct Answer: A  🗳️

      Question #2

      Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
      You need to evaluate the significance of coefficients that are produced by using a model that was estimated already.
      Which function should you use?

      • A. rxTransform
      • B. stepAic
      • C. summary
      • D. rxLogit
      • E. rxPredict
      • F. rxTweedie
      • G. rxDataStep
      • H. rxLinMod
      Reveal Solution  Discussion  0

      Correct Answer: H  🗳️

      Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

      Question #3

      Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
      After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
      You use dplyrXdf, and you discover that after you exit the session, the output files that were created were deleted.
      You need to prevent the files from being deleted.
      Solution: You use rxSetComputeContext with the local parameter before performing operations that save results.
      Does this meet the goal?

      • A. No
      • B. Yes
      Reveal Solution  Discussion  0

      Correct Answer: A  🗳️

      Question #4

      Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
      You have a data source that is larger than memory.
      You need to visualize the distribution of the values for a variable in the data source.
      What should you use?

      • A. the rxHistogram function
      • B. the rxCrossTabs function
      • C. the summary function
      • D. the rxCube function
      • E. the Describe package
      • F. the ggplot2 package
      • G. the rxQuantile function
      • H. the rxSummary function
      Reveal Solution  Discussion  0

      Correct Answer: A  🗳️

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