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Analyzing Big Data with Microsoft R 70-773 Exam
Analyzing Big Data with Microsoft R 70-773 Exam been designed in order to test expertise and technical knowledge in designing and implementing Microsoft services in order to obtain value from the available data set. It examines the candidate's ability to execute Microsoft Big Data Services according to architecture practices. The Analyzing Big Data with Microsoft R 70-773 Exam is high level exam and it requires in-depth knowledge of data analytics concepts, before you go ahead and write this certification you must require some prerequisites Candidates for this exam are data scientists or analysts who process and analyze data sets larger than memory using R.
Candidates should have experience with R, familiarity with data structures, familiarity with basic programming concepts (such as control flow and scope), and familiarity with writing and debugging R functions. Candidates should be familiar with common statistical methods and data analysis best practices. Candidates should also have a high-level understanding of data platforms, such as the Hadoop ecosystem, SQL Server, and core T-SQL capabilities. We think our Analyzing Big Data with Microsoft R 70-773 Exam Practice Test Paper and Dumps will provide you 100% confidence to make you appear for Microsoft 70-773 Exam
This is the list of the contents in our Analyzing Big Data with Microsoft R 70-773 Practice Test:
- Data Processing with RxDataStep.
- Models with ScaleR.
- Data reading with R Server.
- Compute concepts to Run R Server.
- Hadoop Ecosystem and Spark.
Reference: https://www.microsoft.com/en-us/learning/exam-70-773.aspx
Overview about MICROSOFT 70-773 Exam
- Registration Fee: 165 USD
- Format: Multiple choice, multiple answer
- Length of Examination: 150 minutes
- Number of Questions: 40-60
- Passing Score: 70-80%
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Microsoft 070-773 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Use R Server in Different Environments | - Perform in-database analytics using SQL Server - Deploy predictive models to SQL Server and Azure Machine Learning - Implement analysis workflows in Hadoop and Spark - Use different compute contexts to run R Server effectively - Optimize tasks using local compute contexts |
| Build Predictive Models with ScaleR | - Estimate linear models - Generate predictions and residuals - Evaluate models and tuning parameters - Create additional models using MicrosoftML packages - Build and use partitioning models |
| Read and Explore Big Data | - Summarize data - Read data with R Server - Visualize data |
| Process Big Data | - Process text using MicrosoftML packages - Manage data sets - Perform complex transforms using transform functions - Process data with rxDataStep |
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