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The Design and Implement Big Data Analytics Solutions (70-475日本語版) certification exam is designed for professionals who are responsible for designing, building, and deploying big data analytics solutions. These solutions must be able to analyze data and extract insights that can drive business decisions. The 070-475 exam is intended for professionals who have experience working with big data technologies such as Hadoop, Spark, and Azure Data Lake. Design and Implement Big Data Analytics Solutions (70-475日本語版) certification exam is also ideal for professionals who work with SQL Server and other relational databases to create big data solutions.

Microsoft 070-475 certification exam is designed for professionals who are interested in validating their skills and knowledge in designing and implementing big data analytics solutions. Design and Implement Big Data Analytics Solutions (70-475日本語版) certification exam covers a wide range of topics such as data analysis, data storage, data processing, and data visualization. Candidates who pass 70-475J exam will demonstrate their ability to design and implement big data analytics solutions that meet the needs of their organizations.

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Microsoft 070-475 exam is a challenging test that evaluates an individual’s ability to design and implement big data analytics solutions using Microsoft technologies. Passing 70-475J exam can help you earn the MCSE: Data Management and Analytics certification and demonstrate your expertise in big data analytics. To prepare for the exam, Microsoft offers a variety of training resources and study materials that can help you succeed.

Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx

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Microsoft 70-475日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design Big Data Batch Processing and Interactive Solutions20-25%- Design interactive queries for big data
- Design for data security
- Ingest data for batch and interactive processing
- Design for batch processing
- Design and provision compute clusters
Topic 2: Operationalize End-to-End Cloud Analytics Solutions25-30%- Design deployment strategies
- Move, transform, and analyze data
- Create and configure Azure Data Factory
- Orchestrate data processing workflows
- Monitor and manage data pipelines
Topic 3: Design Machine Learning Solutions25-30%- Determine pre-processing and training locations
- Apply custom processing with R and Python
- Create and manage experiments
- Select input/output data types
- Publish machine learning web services
Topic 4: Design Big Data Real-Time Processing Solutions25-30%- Design for Lambda architecture
- Design for real-time processing
- Ingest data for real-time processing
- Design and provision compute resources

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