Perform Data Engineering on Microsoft Azure HDInsight 70-775 Dumps will include below mentioned topics with Exam focused percentage
- Implement Big Data Interactive Processing Solutions: 20-25%
- Use Other Services for Machine Learning: 20-25%
- Implement Big Data Batch Processing Solutions: 20-25%
- Administer and Provision HDInsight Clusters: 20-25%
Reference: https://www.microsoft.com/en-us/learning/exam-70-775.aspx
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Perform Data Engineering on Microsoft Azure HDInsight 70-775 Dumps Provided Study Notes
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- OMS
- Eventhub
- Kafka
- Azure Datafactory
- Spark Datasets
- Hadoop Services
- Azure ARM Templates
- HDInsight Cluster
- Azure DataLake
- BI Tools
- Hbase
- Azure Storage
- Hive Tables
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Overview about MICROSOFT 70-775 Exam
- Registration Fee: 165 USD
- Passing Score: 70-80%
- Number of Questions: 40-60
- Format: Multiple choice, multiple answer
- Length of Examination: 120 minutes
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Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam
Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam is centered around Big Data Analytic framework which is one of the hottest topics and technology areas in the industry. Azure HDInsight is one of the services within the Microsoft Azure platform that services the ability to build scalable, Big Data solutions in the cloud. In an effort to expand out the breadth of certifications and exams offered around Microsoft Azure, the cloud, and Big Data, Microsoft has added the Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam.
This certification exam is targeted towards data engineers, data architects, data scientists, and data developers who implement big data engineering workflows on HDInsight. Candidates for this exam should have relevant work experience in big data analytics solutions. Candidates should also be familiar with the features and capabilities of batch data processing, real-time processing, and interactive processing. Candidates who take this exam are expected to be able to apply the Microsoft cloud ecosystem to design and implement big data engineering workflows and to use open source technologies for strategic value-add. This exam only available for the candidates till 30th June 2019 after that this may get replace with some other exam so you can plan get it completed before it get expire.
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This is the list of the contents in our Perform Data Engineering on Microsoft Azure HDInsight 70-775 Practice Test:
- Build Solution that use Hbase
- Data analysis using Hive
- Configure HDInsight clusters
- Spark streaming applications using DStream API
- Build solutions that use Kafka
- Operationalize Hadoop and Spark
- Data analysis using Spark SQL
- Design batch ETL solutions for big data with Spark
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Microsoft 070-775 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Implement Big Data Real-Time Processing Solutions | 25% | - Implement event processing solutions
- 1. Use Apache Storm
- 2. Store and process streaming data with HBase
- 3. Integrate Apache Kafka
- Create Spark Streaming applications
- 1. Implement Structured Streaming
- 2. Use DStreams
- 3. Process streaming data in real time
|
| Administer and Provision HDInsight Clusters | 25% | - Secure and manage multi-user clusters
- 1. Manage user authorization and permissions
- 2. Configure domain-joined clusters
- 3. Use Ambari and Ranger administration tools
- Deploy and configure HDInsight clusters
- 1. Configure storage and networking
- 2. Customize clusters with script actions
- 3. Create and manage HDInsight cluster types
- Ingest and prepare data
- 1. Load data into Azure Data Lake Store
- 2. Load data into Azure Blob Storage
- 3. Optimize data storage formats
- Monitor and troubleshoot clusters
- 1. Monitor resources with Operations Management Suite
- 2. Analyze HDInsight logs
- 3. Use YARN logs and heap dumps
|
| Implement Big Data Batch Processing Solutions | 25% | - Design ETL solutions with Spark
- 1. Optimize Spark performance
- 2. Process large-scale datasets
- 3. Create Spark ETL processes
- Operationalize Hadoop and Spark workloads
- 1. Automate workflows with Apache Oozie
- 2. Use Azure Data Factory orchestration
- Implement batch processing with Hive and Pig
- 1. Manage data processing workflows
- 2. Execute Pig jobs
- 3. Design Hive-based solutions
|
| Implement Big Data Interactive Processing Solutions | 25% | - Create interactive query solutions
- 1. Use Interactive Hive
- 2. Use Spark SQL
- Implement interactive processing on HBase
- 1. Use Apache Phoenix
- 2. Query HBase data efficiently
- Perform exploratory data analysis
- 1. Work with Jupyter notebooks
- 2. Analyze data with Spark SQL
- 3. Use Hive for exploration
- 4. Use Apache Zeppelin
|