Big Data and hadoop Training in New Orleans, LA| bootcamp…

Next class starting January 12, 2019 Delivery Method This course will be delivered through LIVE Instructor Led Online Training. There will be 8 online sessions, each session being of 2 hours. Each session will have presentation about theory, concepts and technology, followed by Hands-on Lab practice exercises. Each session will be recorded and the recordings, along with training material, code samples, will be uploaded on Microsoft cloud and shared with students. Duration 16 hours over 4 weekends Class Schedule January 12,13,19,20,26,27 Saturday and Sunday each weekend 10:00 AM – 12:00 PM US Eastern time each day Please check your local date and time for first session Video Conference Details Will be sent once you register and payment is received Audience This course is meant for IT professionals who are Database Administrators, Systems Admins, Developers, Testers, Solutions Architect, Release Engineers, Cloud Professionals and others who want to build a career in big data and hadoop. Course Prerequisites Desired but not required – Exposure to, Working proficiency of BI, sql, scripting, how to handle and manage data and databases, using Excel.   Some activities will require some prior programming experience, preferably in Python or Scala. A basic familiarity with the Linux command line will be very helpful. You will need access to a PC running 64-bit Windows, MacOS, or Linux with an Internet connection, if you want to participate in the hands-on activities and exercises. You must have at least 8GB of free RAM on your system; 10GB or more is recommended. If your PC does not meet these requirements, you can still follow along in the course without doing hands-on activities. Software access A Microsoft cloud Azure account will be provided to every student where they will install hortonworks hadoop on the cloud virtual machines. Students will carry out the hands-on lab exercises with instructor guidance. Course Outline 1. Big Data Basics An introduction to Big Data? Why is Big Data? Why now? The Three Dimensions of Big Data (Three Vs) Evolution of Big Data  Big Data versus Traditional RDBMS Databases Big Data versus Traditional BI and Analytics Big Data versus Traditional Storage  Key Challenges in Big Data adoption Benefits of adoption of Big Data Introduction to Big Data Technology Stack Apache Hadoop Framework Introduction to Microsoft HDInsight – Microsoft’s Big Data Service Hands-On Lab: Creating Azure Storage Account Creating HDInsight Cluster Using services on HDInsight Cluster 2. The Big Data Technology Stack Basics of Hadoop Distributed File System (HDFS) Basics of Hadoop Distributed Processing (Map Reduce Jobs) Hands-On Lab: Loading files to Azure storage account Moving files across HDInsight Cluster  Remote Access to Azure Storage Account and HDInsight Cluster 3. Deep dive into Hadoop Storage System (HDFS) (1 Hour) HDFS Reading files with HDFS Writing files with HDFS Error Handling Hands-On Lab: Accessing Hadoop configuration files using HDInsight Cluster 4. Processing Big Data –MapReduce and YARN How MapReduce works Handling Common Errors  Bottlenecks with MapReduce How YARN (MapReduceV2) works Difference between MR1 and MR2 Error Handling Hands-On Lab: Running a simple MapReduce application (word count) Running a custom MapReduce application (census data) Running MapReduce via PowerShell Running a MapReduce application using PowerShell Monitoring application status 5. Big Data Development Framework Introduction to HIVE  Introduction to PIG  HBase Hands-On Lab: Loading the data into HIVE Submitting Pig jobs using HDInsight Submitting Pig jobs via PowerShell 6. Big Data Integration and Management Big Data Integration using Polybase Big Data Management using Ambari Hands-On Lab: Fetching HDInsight data into SQL Using Ambari for managing HDInsight cluster 7. Store and query your data with Sqoop, Hive, MySQL, 8. Design real-world systems using the Hadoop ecosystem 9. Learn how your cluster is managed with YARN, Mesos, Zookeeper, 10. Handle streaming data in real time with Kafka, Spark Streaming Student Advantage 1. Class recordings will be made available. 2. Post class support3. Course material available. 4. Software access5. Career advancement and Job placement assistance Refund Policy 100% refund will be provided only if we DO NOT hold the class and/or we reschedule the class and the new dates and timings don’t work for you.  If the class is held as per schedule, you don’t show up or you register, purchase a training ticket and then change your mind, we will not issue a refund.

Publicado en Events |