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Actualkey Prepration Latest 70-475 : Designing and Implementing Big Data Analytics Solutions Questions and Answers PDF's, Verified Answers via Experts - Pass Your Exam For Sure and instant Downloads - "Money Back Guarantee".
| Vendor | Microsoft |
| Certification | Microsoft Certified Professional |
| Exam Code | 70-475 |
| Title | Designing and Implementing Big Data Analytics Solutions |
| No Of Questions | 122 |
| Last Updated | July 1,2024 |
| Product Type | Q & A with Explanation |
| Bundel Pack Included | PDF + Offline / Andriod Testing Engine and Simulator |
Exam 70-475
Designing and Implementing Big Data Analytics Solutions
Languages: English, Chinese (Simplified), Chinese (Traditional), French, German, Japanese, Portuguese (Brazil), Spanish, Russian
Audiences: IT Professionals
Technology: Microsoft Azure
Credit toward certification: MCP, MCSA, MCSE
This Training Covers
This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area on the exam. The higher the percentage, the more questions you are likely to see on that content area on the exam. View video tutorials about the variety of question types on Microsoft exams.
Please note that the questions may test on, but will not be limited to, the topics described in the bulleted text.
Do you have feedback about the relevance of the skills measured on this exam? Please send Microsoft your comments. All feedback will be reviewed and incorporated as appropriate while still maintaining the validity and reliability of the certification process. Note that Microsoft will not respond directly to your feedback. We appreciate your input in ensuring the quality of the Microsoft Certification program.
If you have concerns about specific questions on this exam, please submit an exam challenge.
If you have other questions or feedback about Microsoft Certification exams or about the certification program, registration, or promotions, please contact your Regional Service Center.
As of February 2017, this exam was updated. To learn more about these changes and how they affect the skills measured, please download and review the exam 70-475 change document.
Design big data batch processing and interactive solutions (30–35%)
Ingest data for batch and interactive processing
Ingest from cloud-born or on-premises data, store data in Microsoft Azure Data Lake, store data in Azure BLOB Storage, perform a one-time bulk data transfer, perform routine small writes on a continuous basis
Design and provision compute clusters
Select compute cluster type, estimate cluster size based on workload
Design for data security
Protect personally identifiable information (PII) data in Azure, encrypt and mask data, implement role-based security, implement row-based security
Design for batch processing
Select appropriate language and tool, identify formats, define metadata, configure output
Design big data real-time processing solutions (30–35%)
Ingest data for real-time processing
Select data ingestion technology, design partitioning scheme, design row key of event tables in HBase
Design and provision compute resources
Select streaming technology in Azure, select real-time event processing technology, select real-time event storage technology, select streaming units, configure cluster size, select the right technology for business requirements, assign appropriate resources for HBase clusters
Design for Lambda architecture
Identify application of Lambda architecture, utilize streaming data to draw business insights in real time, utilize streaming data to show trends in data in real time, utilize streaming data and convert into batch data to get historical view, design such that batch data doesn’t introduce latency, utilize batch data for deeper data analysis
Design for real-time processing
Design for latency and throughput, design reference data streams, design business logic, design visualization output
Operationalize end-to-end cloud analytics solutions (30–35%)
Create a data factory
Identify data sources, identify and provision data processing infrastructure, utilize Visual Studio to design and deploy pipelines, deploy Data Factory Jobs
Orchestrate data processing activities in a data-driven workflow
Leverage data-slicing concepts, identify data dependencies and chaining multiple activities, model complex schedules based on data dependencies, provision and run data pipelines
Monitor and manage the data factory
Identify failures and root causes, create alerts for specified conditions, perform a restatement, start and stop data factory pipelines
Move, transform, and analyze data
Leverage Pig, Hive, MapReduce for data processing; copy data between on-premises and cloud; copy data between cloud data sources; leverage stored procedures; leverage Machine Learning batch execution for scoring, retraining, and update resource; extend the data factory with custom processing steps; load data into a relational store, visualize using Power BI
Design a deployment strategy for an end-to-end solution
Leverage PowerShell for deployment, automate deployment programmatically, design deployment strategies for automation
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