Course: Big Data Fundamentals

$109.00
$131.89 incl. vat

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duration: 5 hours |

Language: English (US) |

access duration: 90 days |

Details

Big Data Fundamentals

(English version)

Target audience

Business Analyst, Manager

Content

Big Data Fundamentals

5 hours

The Big Data Technology Wave

  • start the course
  • put in Big Data into perspective of supercomputing
  • describe Big Data in context of technology waves and put it into the perspective by comparing to previous technology waves
  • list the six emerging technologies and relate them to Big Data
  • define big data and describe Gartner's Vectors
  • define structured and unstructured data in terms of Gartner's model
  • list the standard sizes used in Big Data to determine sizes of data sets
  • list the three primary key contributors to the origins of Big Data
  • list the primary Big Data distro companies
  • describe the Apache Software Foundation
  • list projects attributable to the Apache Software Foundation
  • list projects attributable to the Apache Software Foundation
  • describe Cascading and MongoDB
  • list the layers of the Big Data Stack
  • list the common Big Data components
  • describe columnar databases and Hbase
  • describe solutions for scaling computing
  • describe the design principles of Hadoop
  • map out the functional view of Hadoop
  • describe the architecture of HDFS
  • describe the architecture of Yarn
  • describe the attributes and processes of MapReduce
  • describe the architecture of Spark
  • describe Big Data in a historical context and the tools available for working with Big Data

Big Data Opportunities and Challenges

  • start the course
  • list the team members in a Big Data team, and describe their interrelationship
  • list the team members in a Big Data business team, and describe their interrelationship
  • list the team members in a Big Data analytics team, and describe their interrelationship
  • list the team members in a Big Data architects team, and describe their interrelationship
  • list the team members in a Big Data Hadoop operators team, and describe their interrelationship
  • describe the factors impacting Big Data teams
  • describe DIY supercomputing Big Data projects
  • describe the use of Hadoop in cloud computing
  • describe data warehousing for Big Data
  • identify the key factors in the costs of Big Data
  • assess relational database management systems in the context of Big Data
  • assess Big Data infrastructure projects
  • describe data mining
  • describe Big Data recommendation engines
  • describe common use cases for Big Data analytics
  • describe the global impact of Big Data
  • describe the global increase in produced data volume
  • list the main companies involved in Big Data
  • identify Big Data business opportunities
  • describe the Big Data physical challenges to be overcome
  • describe the privacy and security challenges of Big Data
  • describe the required planning activities for Big Data
  • describe Big Data industry trends
  • describe and identify the challenges and opportunities presented by Big Data

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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