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Big data is a term for data sets so large that traditional data processing applications can not be used to perform any sort of analysis. It is often semi structured or unstructured in form. There are a number of unique challenges that arise when companies begin to use big data. The least of which are the engineering concerns. This course will introduce some of those engineering challenges and describe how some companies have come up with solutions.

Learning Objectives
  • Start the course
  • Describe big data and the three v's
  • Recall what factors are important when considering a big data infrastructure
  • Recall some of the options when building a cloud based big data infrastructure
  • Compare the pros and cons of building an in house big data infrastructure
  • Recall the skill sets that individuals should have to make up the big data team
  • Describe the different software options that are available for big data analytics
  • Recall the types of analytics that can be done with the data
  • Compare the different types of data visualization that can be done with the analytics
  • Recall how large companies have used big data analytics effectively
  • Describe the risks involved when considering using big data as a solution
  • Understand big data engineering concerns, such as choosing storage and software
  • Audience

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