Perform Data Engineering on Microsoft Azure HDInsight 70-775 Dumps Provided Study Notes
PassTestking expert team recommend you to prepare some notes on these topics along with it don't forget to practice Perform Data Engineering on Microsoft Azure HDInsight 70-775 Dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.
- Kafka
- Hbase
- Azure Storage
- Azure ARM Templates
- Hadoop Services
- Eventhub
- Azure DataLake
- BI Tools
- Azure Datafactory
- HDInsight Cluster
- Hive Tables
- OMS
- Spark Datasets
Reference: https://www.microsoft.com/en-us/learning/exam-70-775.aspx
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MICROSOFT 70-775 Exam Reference, Microsoft Documents
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Overview about MICROSOFT 70-775 Exam
- Registration Fee: 165 USD
- Number of Questions: 40-60
- Format: Multiple choice, multiple answer
- Length of Examination: 120 minutes
- Passing Score: 70-80%
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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.
We think our Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam Practice Test Paper and Dumps will provide you 100% confidence to make you appear for Microsoft 70-775 Exam.
This is the list of the contents in our Perform Data Engineering on Microsoft Azure HDInsight 70-775 Practice Test:
- Spark streaming applications using DStream API
- Build Solution that use Hbase
- Operationalize Hadoop and Spark
- Design batch ETL solutions for big data with Spark
- Configure HDInsight clusters
- Data analysis using Spark SQL
- Data analysis using Hive
- Build solutions that use Kafka
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Microsoft 70-775 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Administer and Provision HDInsight Clusters | 25% | - Secure and manage multi-user clusters
- 1. Configure domain-joined clusters
- 2. Manage user authorization and permissions
- 3. Use Ambari and Ranger administration tools
- Deploy and configure HDInsight clusters
- 1. Customize clusters with script actions
- 2. Configure storage and networking
- 3. Create and manage HDInsight cluster types
- Monitor and troubleshoot clusters
- 1. Use YARN logs and heap dumps
- 2. Monitor resources with Operations Management Suite
- 3. Analyze HDInsight logs
- Ingest and prepare data
- 1. Optimize data storage formats
- 2. Load data into Azure Data Lake Store
- 3. Load data into Azure Blob Storage
|
| 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. Process streaming data in real time
- 3. Use DStreams
|
| Implement Big Data Interactive Processing Solutions | 25% | - Perform exploratory data analysis
- 1. Use Hive for exploration
- 2. Use Apache Zeppelin
- 3. Work with Jupyter notebooks
- 4. Analyze data with Spark SQL
- Implement interactive processing on HBase
- 1. Query HBase data efficiently
- 2. Use Apache Phoenix
- Create interactive query solutions
- 1. Use Interactive Hive
- 2. Use Spark SQL
|
| Implement Big Data Batch Processing Solutions | 25% | - Implement batch processing with Hive and Pig
- 1. Design Hive-based solutions
- 2. Execute Pig jobs
- 3. Manage data processing workflows
- Operationalize Hadoop and Spark workloads
- 1. Automate workflows with Apache Oozie
- 2. Use Azure Data Factory orchestration
- Design ETL solutions with Spark
- 1. Create Spark ETL processes
- 2. Optimize Spark performance
- 3. Process large-scale datasets
|