FIRST CHAPTER

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FIRST CHAPTER BIG DATA
Richard Xavier
Note by Richard Xavier, updated more than 1 year ago
Richard Xavier
Created by Richard Xavier about 2 years ago
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FACTS - CLASS 2 - There are 2.5 quintillion data per day being generated; - 90% of the data generated on the planet was generated in the last two years; - 80% of data is unstructured or in different formats; - The 4 V's of Big Data -> Volume, Variety, Speed, Veracity; - Volume: Data Size; - Variety: Data Format; - Speed: Data Generation; - Veracity: Data Reliability; - Big data and Data Science are not the same things. - Big Data is the raw material x Data Science is a set of techniques for analyzing data. - When applying Data Science to Big Data, Big Data Analytics is obtained. - Data Engineer -> Extract and store all data - Data Scientist - Process and analyze

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Storage System - Class 3  - It is important in storing data to know how it will be accessed. - structured data is used data warehouse. - unstructured data is used data lake or data store. - Relational Database has schema defined before data storage - Data Warehouse is created by some technology DBMS - Database Management System or (SGBD in Portuguese). - NoSQL Database cannot be unstructured data. - Data Warehouse - stores a large amount of data from different sources. - The goal is to feed business intelligence (The goal: Alimentar). - DW Benefits: Better Business Analytics, Faster Queries, Data Quality Improvements, Historical View. - Data Lake Benefits: Raw Format Storage, Real-time Data Import. - Data Store Benefits: Flexibility. 

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Parallel Storage and Processing - Class 4 - Cluster a set of computers that form a server - Parallel Storage - Distribute storage across multiple servers - Hadoop HDFS- Hadoop Distributed File System cluster manager - You can build a Data Lake that runs on a Cluster and allows you to store large volumes at a low cost. - Job Tracker manages the processing - Task Tracker does the work in the process

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Cloud Computing - Class 5 - Delivery of services over the internet

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Machine Learning - Class 6 - Area that focuses on using data and algorithms to mimic human learning.  

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