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[Special courses] Big Data

  • Lecturer

    Agilewing

  • Course Level

    Solution-based Training

  • ¥6,300.00

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  • Course description
  • Syllabus
  • The Big Data course introduces you to cloud-based big data solutions such as EMR, Redshift, Kinesis, and the rest of the big data platform. In this course, we will show you how to use EMR to process data with a broad system of Hadoop tools such as Hive and Hue. The course also includes how to create a big data environment, how to use DynamoDB, Redshift Quicksight, Athena, and Kinesis in combination, and how to use best practices to design a big data environment for security and economy.
    • Course targets By taking this course, you will be able to:  Cloud vendors solutions within big data systems Use Apache Hadoop in an EMR environment Understanding the components of an EMR cluster  Launch and configure an EMR cluster  Common programming frameworks that leverage EMR, including Hive, Pig, and Streaming  Improve the usability of EMR with Hue Use memory analysis with Spark on EMR Choose the right Cloud vendors data storage option Determine the benefits of using Kinesis to process big data at near real-time  Effectively store and analyze data with Redshift  Understand and manage the costs and security of big data solutions  Protecting big data solutions  Identify options for acquiring, transmitting, and compressing data  Ad Hoc query analysis with Athena  Describe data and queries with visualization software with QuickSight Orchestrate big data workflows with Cloud vendors Data Pipeline
    • Target populationThis course applies to:  The person responsible for designing and implementing a big data solution, the solution architect Data scientists and data analysts are interested in understanding the services and architectural patterns behind big data solutions on Cloud vendorsprerequisites We recommend that those attending this course meet the following prerequisites:  Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, HDFS, and SQL / NoSQL queries  Students should complete Big Data Technology Fundamentals online training or have equivalent experience  Experience with core Cloud vendors services and public cloud implementation  Students should complete Cloud vendors Technical Essentials courses or have equivalent experience  Understand the basic teaching methods of data warehouse, relational database system and database design This course will be taught in combination with:  Instructor-led training (ILT)  Hands-on lab Hands-on activities This course allows you to experiment with new technologies and apply what you have learned to your work environment through various practical exercises
    • Course OutlineDay 1 Big data overview  Big data acquisition and transmission Big data streaming and Kinesis Lab 1: Stream and analyze Apache server log data with Kinesis  Big data storage solutions  Big data processing and analysis Lab 2: Querying S3 Log Data with AthenaDay 2  Apache Hadoop and EMR Lab 3: Store and query data on DynamoDB  Use EMR  Hadoop programming framework Lab 4: Processing server logs with Hive on AEMR  Web interface on EMR Lab 5: Running Pig Scripts in Hue on EMR  Apache Spark on EMR Lab 6: Using Spark on EMR to Process NY Taxi Data Day 3  Redshift and big data  Visualization and compilation of big data  Lab 7: Visualizing Data with TIBCO Spotfire  Manage Big Data Expenses  Protect your deployment  Big data design patterns 3rd day  Redshift and big data  Visualization and compilation of big data  Lab 7: Visualizing Data with TIBCO Spotfire  Manage Big Data Expenses  Protect your deployment  Big data design patterns

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[Special courses] Big Data

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