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Certified Big Data Foundation Training & Certification

Trusted by 1000s of global organizations, NovelVista is the leading Accredited Training Organization (ATO) to conduct Big Data Foundation Training & Certification Course.

  • Industry Expert Trainers
  • Online learning session
  • Accredited Trainer
  • Exam fee included
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📞18002122003
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9000+ Professionals Enrolled

Certified Big Data Foundation Course Overview

Big Data Training and Certification course is targeted towards sharing a vast knowledge of Big Data and its fundamentals. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. When we handle big data, we may not sample but simply observe and track what happens. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value. In our Big Data Foundation training sessions, you’ll learn all about Big Data Fundamentals, Big Data Sources, Data Mining: Concepts and Tools, Big Data Technologies along with Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume, and Sqoop.

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What You Will Get?

Study Material

Mock Exam

16+ hours of live training

Exam registration assistance

Case studies soft copy

Official courseware from GSDC

Learning Outcome

After the completion of the course, the participants would be able to:

How to handle and organize big and complex data.
Big Data guidelines and principles.
Doing structuring and creating databases.
Industry best practices.
Tools and Techniques.
Real-Time Case Studies.

Course Curriculum

Big Data Introduction+

  • Big Data - History, Overview, and Characteristics
  • Definition
  • Benefits
  • Characteristics

Big Data Technology - Overview+

  • Hadoop - Introduction, Usage, Concepts
  • MongoDB - Introduction, Features, Concepts

Big Data - Privacy & Ethics+

  • Privacy - Compliance
  • Privacy - Challenges
  • Privacy - Approach
  • Ethics

Sources for Big Data+

  • Enterprise Data Sources
  • Enterprise Systems
  • Oracle
  • SAP
  • Microsoft
  • Data Warehouses
  • Unstructured Data
  • Metadata

Social Media Data Sources+

  • Introduction
  • Facebook - Introduction, Public Feed API, Keyword Insights API, Graph API
  • Twitter - Introduction, Streaming APIs, REST APIs
  • Other Social Media Sources

Public Data Sources+

  • Introduction
  • Weather
  • Economics
  • Finance
  • Regulatory Bodies

Data Mining - Concepts and Tools+

  • Data Mining - Introduction
  • Types of Data Mining - Overview
  • Classification
  • Association
  • Clustering
  • Weka
  • Modules of Weka Applications
  • KNIME
  • R Language

Big Data Technologies - Hadoop+

  • Introduction
  • Main Components of Hadoop
  • Additional Components of Hadoop
  • How to Install and Configure
  • Map Reduce

Data Processing with Hadoop+

  • Introduction
  • Twitter Sentiment Analysis - Overview & Algorithm
  • Network Log Analysis - Overview & Algorithm

Big Data Technologies - MongoDB+

  • MongoDB Fundamentals
  • Install & Configure
  • Introduction
  • Replication
  • Sharding
  • Sharding and Replication
  • MongoDB Ecosystem - Languages and Drivers
  • MongoDB Ecosystem - Hadoop Integration
  • MongoDB Ecosystem - Tools

Document Databases+

  • Introduction
  • Documents
  • Document Design Considerations
  • Fields

Data Modelling with Document Databases+

  • Introduction
  • Twitter Sentiment Analysis with Algorithm
  • Network Log Analysis with Algorithm