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IBM BigInsights Foundation - SPVC

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This training course is for those who want a foundation of IBM BigInsights. This course consists of two separate modules. The first module is IBM BigInsights Overview and it will give you an overview of IBM's big data strategy as well as a why it is important to understand and use big data. It will cover IBM BigInsights as a platform for managing and gaining insights from your big data. As such, you will see how the BigInsights have aligned their offerings to better suit your needs with the IBM Open Platform (IOP) along with the three specialized modules with value-add that sits on top of the IOP. Along with that, you will get an introduction to the BigInsights value-add including Big SQL, BigSheets, and Big R. The second module is IBM Open Platform with Apache Hadoop. IBM Open Platform (IOP) with Apache Hadoop is the first premiere collaborative platform to enable Big Data solutions to be developed on the common set of Apache Hadoop technologies. The Open Data Platform initiative (ODP) is a shared industry effort focused on promoting and advancing the state of Apache Hadoop and Big Data technologies for the enterprise. The current ecosystem is challenged and slowed by fragmented and duplicated efforts between different groups. The ODP Core will take the guesswork out of the process and accelerate many use cases by running on a common platform. It allows enterprises to focus on building business driven applications. This module provides an in-depth introduction to the main components of the ODP core --namely Apache Hadoop (inclusive of HDFS, YARN, and MapReduce) and Apache Ambari -- as well as providing a treatment of the main open-source components that are generally made available with the ODP core in a production Hadoop cluster. IBM BigInsights v4 itself is built upon the ODP core and these other main open-source components.The relationships between the IBM Open Platform with Apache Hadoop and the BigInsights add-ons is covered briefly in Unit 1 – pro . If...

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· A chi è diretto?

This intermediate course is for those who want a foundation of IBM BigInsights. This includes the following and those who are interested in learning about IBM's Open Platform with Apache Hadoop: Big data engineers Data scientist Developers or programmers Administrators This course consists of two separate modules. The first module is IBM BigInsights Overview and it will give you an overview of IBM's big data strategy as well as a why it is important to understand and use big data. The second module is IBM Open Platform with Apache Hadoop. IBM Open Platform (IOP) with Apache Hadoop is the first premiere collaborative platform to enable Big Data solutions to be developed on the common set of Apache Hadoop technologies.

· Requisiti

There are no pre-requisites for this course. However, knowledge of Linux would be beneficial.

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Cosa impari in questo corso?

Open source
Apache
SQL

Programma

IBM BigInsights Overview (DW6A1) Unit 1: Introduction to Big Data Exercise 1: Setting up the lab environment Unit 2: Introduction to IBM BigInsights Exercise 2: Getting started with IBM BigInsights Unit 3: IBM BigInsights for Analysts Exercise 3: Working with Big SQL and BigSheets Unit 4: IBM BigInsights for Data Scientist Exercise 4: Analyzing data with Big R, Jaql, and AQL Unit 5: IBM BigInsights for Enterprise Management IBM Open Platform with Apache Hadoop (DW6B1) Unit 1: IBM Open Platform with Apache Hadoop Exercise 1: Exploring the HDFS Unit 2: Apache Ambari Exercise 2: Managing Hadoop clusters with Apache Ambari Unit 3: Hadoop Distributed File System Exercise 3: File access & basic commands with HDFS Unit 4: MapReduce and Yarn Topic 1: Introduction to MapReduce based on MR1 Topic 2: Limitations of MR1 Topic 3: YARN and MR2 Exercise 4: Creating and coding a simple MapReduce job Possibly a more complex second Exercise Unit 5: Apache Spark Exercise 5: Working with Spark's RDD to a Spark job Unit 6: Coordination, management, and governance Exercise 6: Apache ZooKeeper, Apache Slider, Apache Knox Unit 7: Data Movement Exercise 7: Moving data into Hadoop with Flume and Sqoop Unit 8: Storing and Accessing Data Topic 1: Representing Data: CSV, XML, JSON, & YAML Topic 2: Open Source Programming Languages: Pig, Hive, & Other [R, Python, etc] Topic 3: NoSQL Concepts Topic 4: Accessing Hadoop data using Hive Exercise 8: Performing CRUD operations using the HBase shell Topic 5: Querying Hadoop data using Hive Exercise 9: Using Hive to Access Hadoop / HBase Data Unit 9: Advanced Topics Topic 1: Controlling job workflows with Oozie Topic 2: Search using Apache Solr No lab exercises


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