Edureka Fan

Edureka Fan


Hadoop Tutorial For Beginners - Big Data & Hadoop Full Course

This Edureka Big Data & Hadoop Full Course video will help you understand and learn Hadoop concepts in detail. This Big Data & Hadoop Tutorial is ideal for both beginners as well as professionals who want to master the Hadoop Ecosystem. Below are the topics covered in this Big Data & Hadoop Tutorial for Beginners video:

  • 00:00 Agenda
  • 2:37 Introduction to Big Data
  • 8:22 What is Big Data?
  • 9:32 5 V’s of Big Data
  • 15:02 Big Data as an Opportunity
  • 18:27 IBM Big Data Analytics Use-Case
  • 24:38 Big Data Analytics & Use-Case
  • 32:43 What is Big Data Analytics?
  • 33:28 Stages of Big Data Analytics
  • 34:33 Types of Big Data Analytics
  • 39:53 Big Data Analytics in Different Domains
  • 46:38 Problems with Big Data: Restaurant Analogy
  • 54:53 Apache Hadoop
  • 56:18 Hadoop Master-Slave Architecture
  • 1:00:38 HDFS
  • 1:01:03 NameNode & DataNode
  • 1:02:33 Secondary Namenode & Checkpointing
  • 1:06:18 HDFS Data Blocks
  • 1:11:18 HDFS Replication
  • 1:12:48 HDFS Read/Write Mechanism
  • 1:20:43 MapReduce
  • 1:24:33 What is MapReduce?
  • 1:25:43 MapReduce Word Count Program
  • 1:42:13 YARN
  • 1:43:38 MapReduce Job Workflow
  • 1:47:28 YARN Architecture
  • 1:48:33 Hadoop Architecture
  • 1:49:38 Hadoop Ecosystem
  • 1:50:53 Hadoop Cluster Mode
  • 1:52:33 Hadoop Ecosystem
  • 1:55:38 Hadoop Installation
  • 2:08:03 MapReduce Examples
  • 2:08:08 Weather Data Set Analysis
  • 2:16:23 MapReduce Last.FM Example
  • 2:24:13 Apache Sqoop Tutorial
  • 2:26:03 What is Sqoop?
  • 2:27:33 Features of Sqoop
  • 2:28:43 Sqoop Architecture
  • 2:30:48 Import Sqoop Command
  • 2:38:23 Export Sqoop Command
  • 2:40:03 List Database Command
  • 2:42:28 Apache Flume Tutorial
  • 2:45:18 Flume Architecture
  • 2:46:58 Flume Twitter Streaming
  • 2:52:23 Apache Pig Tutorial
  • 2:55:18 Pig vs MapReduce
  • 2:58:23 Twitter Case Study
  • 3:04:48 Pig Architecture
  • 3:05:48 Pig Components
  • 3:09:38 Pig Data Models
  • 3:14:33 Pig Commands
  • 3:27:33 Apache Hive Tutorial
  • 3:40:43 What is Hive?
  • 3:43:23 PigLatin Vs HiveQL
  • 3:47:09 Hive Architecture
  • 3:50:19 Hive Components
  • 3:51:24 Metastore
  • 3:55:44 Hive Commands
  • 3:56:44 Hive Setup
  • 4:01:04 Type Systems
  • 4:02:54 Hive Data Models
  • 4:46:54 Hive Partitioning
  • 4:56:44 Bucketing in Hive
  • 5:44:19 External Table
  • 5:48:49 Apache HBase Tutorial
  • 6:13:05 Types of NoSQL Databases
  • 6:21:36 History if HBase
  • 6:23:06 HBase vs RDBMS
  • 6:27:56 Uses of HBase
  • 6:31:46 Companies Using HBase
  • 6:41:03 HBase Operation
  • 6:51:28 HBase Shell
  • 7:16:38 Single Map
  • 7:17:23 Multidimensional Map
  • 7:18:03 Multidimensional Columns
  • 7:20:33 Row vs Column Oriented Databases
  • 7:22:33 HBase Data Models
  • 7:25:03 HBase Physical Storage
  • 7:28:43 HBase Architecture
  • 7:30:48 HBase Components
  • 7:31:04 HBase Read Write Mechanism
  • 7:40:49 Compaction in HBase
  • 7:41:49 HBase Shell
  • 7:42:09 HBase Client API
  • 7:42:24 Hadoop E-Commerce Projects
  • 7:58:24 Distributed Cache
  • 8:00:14 Code Sections
  • 8:17:44 How to Become a Big Data Engineer?
  • 8:18:24 Who is a Big Data Engineer?
  • 8:19:14 Big Data Engineer Responsibilities
  • 8:24:49 Big Data Engineer Skills
  • 8:32:44 Big Data Engineer Learning Path
  • 8:36:19 Big Data & Hadoop Interview Questions

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Hadoop Tutorial For Beginners - Big Data & Hadoop Full Course

What is the cost of Hadoop Training in India?

Hadoop is an open-source setting that delivers exceptional data management provisions. It is a framework that assists the processing of vast data sets in a circulated computing habitat. It is built to enhance from single servers to thousands of machines, each delivering computation, and storage. Its distributed file system enables timely data transfer rates among nodes and permits the system to proceed to conduct unbroken in case of a node failure, which minimizes the risk of destructive system downfall, even if a crucial number of nodes become out of action. Hadoop is very helpful for massive scale businesses founding on its proven usefulness for enterprises given below:

Benefits for Enterprises:

● Hadoop delivers a cost-effective storage outcome for a business.
● It promotes businesses to handily access original data sources and tap into numerous categories of data to generate value from that data.
● It is a highly scalable storage setting.
● The distinctive storage procedure of Hadoop is established on a distributed file system that basically ‘maps’ data wherever it is discovered on a cluster. The tools for data processing are often on similar servers where the data is located, occurring in the much faster data processing.
● Hadoop is now widely operated across enterprises, including finance, media and entertainment, government, healthcare, information services, retail, and other commerce
● Hadoop is fault tolerance. When data is delivered to an individual node, that data is also reproduced to other nodes in the cluster, which implies that in the event of loss, there is another copy accessible for usage.
● Hadoop is more than just a rapid, affordable database and analytics device. It is composed of a scale-out architecture that can affordably reserve all of a company’s data for later usage.

Join Big Data Hadoop Training Course to get hands-on experience.

Demand for Hadoop:

Low expense enactment of the Hadoop forum is tempting the corporations to acquire this technology more conveniently. The data management enterprise has widened from software and web into retail, hospitals, government, etc. This builds an enormous need for scalable and cost-effective settings of data storage like Hadoop.
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Big Data Hadoop Training Course at KVCH is administered by Experts who provide Online training for big data. KVCH offers Extensive Big Data Hadoop Online Training to learn Big data Hadoop architecture.
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KVCH’s Advanced Big Data Hadoop Online Training is packed with Best in Industry Certified Professionals who have More than 20+ Big Data Hadoop Industry Experience who Can Provide Real-time Experience As per The Current Industry Needs.

Are you the one who is very passionate to learn Big Data Hadoop Technology from scratch? The one who is eager to understand how this technology functions? Then you’re landed in the right place where you can enhance your skills in this field with KVCH’s Advanced Big Data Hadoop Online Training.
Enroll in Big Data Hadoop Certification Training and receive a Global Certification.
Improve your career progress by discovering the most strenuous technology i.e. Big Data Hadoop Course from the industry-certified experts of Best Big Data Hadoop Online Training. So, choose KVCH the best coaching center and get advanced course complete certification with 100% Job Assistance.

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● Get trained by the finest qualified professionals
● 100% practical training
● Flexible timings
● Cost-Efficient
● Real-Time Projects
● Resume Writing Preparation
● Mock Tests & interviews
● Access to KVCH’s Learning Management System Platform
● Access to 1000+ Online Video Tutorials
● Weekend and Weekdays batches
● Affordable Fees
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Extensively narrating the IT world presently gets upgraded with ever-renewing technologies every minute. If one lacks much familiarity in coding and doesn’t have an adequate hands-on scripting understanding but still wishes to make an impression in the technical business that too in the IT sector, Big Data Hadoop Online Training is perhaps the niche one requires to begin at. Taking up professional Big Data Training is thus the best option to get to the depth of this language. If one doesn’t have much acquaintance in coding and doesn’t have a good hands-on scripting experience but still wants to make a mark in the technical career that too in the IT sector, Hadoop Corporate Training is probably the place one needs to start at. Adopting skilled Big Data Hadoop Online Training is therefore the promising possibility to get to the center of this language.

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akshay L

akshay L


Big Data & Hadoop Full Course | Hadoop Training | Big Data Tutorial | Intellipaat

In this hadoop training, you will learn big data & hadoop full course right from beginning to all the advanced concepts with hands on demo. There is a project as well at the end so that you can master this technology. This hadoop training will help you learn hadoop in 12 hours completely.

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 iOS App Dev

iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

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Sival Alethea

Sival Alethea


Learn Data Science Tutorial - Full Course for Beginners. DO NOT MISS!!!

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the “sexiest job of the 21st century.” You’ll learn the important elements of data science. You’ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You’ll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science

  • Welcome (1.1)
  • Demand for Data Science (2.1)
  • The Data Science Venn Diagram (2.2)
  • The Data Science Pathway (2.3)
  • Roles in Data Science (2.4)
  • Teams in Data Science (2.5)
  • Big Data (3.1)
  • Coding (3.2)
  • Statistics (3.3)
  • Business Intelligence (3.4)
  • Do No Harm (4.1)
  • Methods Overview (5.1)
  • Sourcing Overview (5.2)
  • Coding Overview (5.3)
  • Math Overview (5.4)
  • Statistics Overview (5.5)
  • Machine Learning Overview (5.6)
  • Interpretability (6.1)
  • Actionable Insights (6.2)
  • Presentation Graphics (6.3)
  • Reproducible Research (6.4)
  • Next Steps (7.1)

⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)

  • Welcome (1.1)
  • Metrics (2.1)
  • Accuracy (2.2)
  • Social Context of Measurement (2.3)
  • Existing Data (3.1)
  • APIs (3.2)
  • Scraping (3.3)
  • New Data (4.1)
  • Interviews (4.2)
  • Surveys (4.3)
  • Card Sorting (4.4)
  • Lab Experiments (4.5)
  • A/B Testing (4.6)
  • Next Steps (5.1)

⌨️ Part 3: Coding (2:32:42)

  • Welcome (1.1)
  • Spreadsheets (2.1)
  • Tableau Public (2.2)
  • SPSS (2.3)
  • JASP (2.4)
  • Other Software (2.5)
  • HTML (3.1)
  • XML (3.2)
  • JSON (3.3)
  • R (4.1)
  • Python (4.2)
  • SQL (4.3)
  • C, C++, & Java (4.4)
  • Bash (4.5)
  • Regex (5.1)
  • Next Steps (6.1)

⌨️ Part 4: Mathematics (4:01:09)

  • Welcome (1.1)
  • Elementary Algebra (2.1)
  • Linear Algebra (2.2)
  • Systems of Linear Equations (2.3)
  • Calculus (2.4)
  • Calculus & Optimization (2.5)
  • Big O (3.1)
  • Probability (3.2)

⌨️ Part 5: Statistics (4:44:03)

  • Welcome (1.1)
  • Exploration Overview (2.1)
  • Exploratory Graphics (2.2)
  • Exploratory Statistics (2.3)
  • Descriptive Statistics (2.4)
  • Inferential Statistics (3.1)
  • Hypothesis Testing (3.2)
  • Estimation (3.3)
  • Estimators (4.1)
  • Measures of Fit (4.2)
  • Feature Selection (4.3)
  • Problems in Modeling (4.4)
  • Model Validation (4.5)
  • DIY (4.6)
  • Next Step (5.1)

📺 The video in this post was made by
The origin of the article:
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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