Enterprise Database Systems
Big Data Fundamentals
Big Data Opportunities and Challenges
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The Big Data Technology Wave
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Big Data Opportunities and Challenges
Lesson Objectives
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
Overview/Description
Big Data requires a holistic approach and a change to regular working practices. This course covers the way teams work in Big Data organizations, some projects and use cases for Big Data, and challenges and opportunities that Big Data presents.
Big Data requires a holistic approach and a change to regular working practices. This course covers the way teams work in Big Data organizations, some projects and use cases for Big Data, and challenges and opportunities that Big Data presents.
Target Audience
IT engineers, programmers, and DBAs working with or interested in Big Data, as well as business decision makers interested in implementing or managing Big Data systems
IT engineers, programmers, and DBAs working with or interested in Big Data, as well as business decision makers interested in implementing or managing Big Data systems
The Big Data Technology Wave
Lesson Objectives
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
Overview/Description
A number of tools are available for working with Big Data. Many of the tools are open source and Linux distribution based. This course covers the fundamentals of Big Data, including positioning it in a historical IT context, the tools available for working with Big Data, the Big Data stack, and finally, an in-depth look at Apache Hadoop.
A number of tools are available for working with Big Data. Many of the tools are open source and Linux distribution based. This course covers the fundamentals of Big Data, including positioning it in a historical IT context, the tools available for working with Big Data, the Big Data stack, and finally, an in-depth look at Apache Hadoop.
Target Audience
IT engineers, programmers, and DBAs working with or interested in Big Data, as well as business decision makers interested in implementing or managing Big Data systems
IT engineers, programmers, and DBAs working with or interested in Big Data, as well as business decision makers interested in implementing or managing Big Data systems
