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Big Data Fundamentals (BDF)

Contenuti dettagliati del Corso

Giorno 1

  • Course introduction
  • Fundamentals of Big Data
    • What is Big Data?
    • 3 V of the Big Data
    • Data at Rest and Data in Transit
  • The Waves of Managing Big Data
    • Creating manageable data structures
    • Web and Content Management
    • Managing Big Data
    • Virtualization for Big Data
    • Cloud Computing for Big Data
  • Building a Data Story
    • Deductive reasoning
    • Inductive Reasoning
    • The Power of Visualization
  • Big data Architecture Overview
    • Capture, organize, integrate, analyze an act
    • Setting the Architectural foundation (Architectural Framework)
    • Performances. Introducing MapReduce, Hadoop and Big Table
    • Analytics. Big Data Analytics Concepts, Reporting and Visualizaztion, BigData applications.
  • Data Ingestion, transfer and compression.
    • Overview: ingesting data
    • Best Practices for ingesting data
    • MySQL VS NoSQL DataBase
    • Data Ingestion Tools
    • Data Store Type
  • Hadoop & Map Reduce Fundamentals
    • Hadoop EcoSystem
    • Map Function and Reduce Function
    • MapReduce VS RMDBS

Giorno 2

  • Let’s introduce JSON.
    • Meaning of JavaScript Object Notation
    • Analyzing a json template
    • NoSQL Database and JSON
    • MongoDB and BSON
  • Streaming Architecture and Streaming Data (LAB).
    • Kafka, Spark and ELK stack from Elastic
    • Ingest Data
    • Setting Up streaming architecture
    • Shard Allocation
  • Learning From Data, Introduction to Machine Learning.
    • Adding Machine Learning to your Architecture
    • Predictive Analytics
    • Types of Machine Learning Analysis
    • Common Applications of Machine Learning
    • Error in Data Analytics
    • Guidelines for Evaluating Results
  • Big Data Solutions in Real World
  • Understanding why Companies needs Big Data
  • Typical Business Use Case