Introduction to Big Data
(Introduction to Big Data)
Interested in increasing your knowledge of the Big Data landscape and improving your English language skills?
This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to:
- Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors.
- Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting.
- Get value out of Big Data by using a 5-step process to structure your analysis.
- Identify what are and what are not big data problems and be able to recast big data problems as data science questions.
- Provide an explanation of the architectural components and programming models used for scalable big data analysis.
- Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model.
- Teacher: Natalia Ilyashenko