Certified Big Data Foundation Training & Certification

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.

Key Features:

• Classroom and virtual  training during weekends
• Study materials accredited by GSDC
• Practice tests to make you certification ready
• Vibrant presentation of real-life case studies

Course Curriculum

Big Data Foundation Training and Certification course’s curriculums are directed towards:

1. Explaining Big Data, its origin, and its characteristics.
2. Discussing the tools applicable to Big Data processing.
3. Explaining data mining.
4. Discussing the popular Big Data technologies like Hadoop and MongoDB.
5. Discussing the Big Data projects and the main players involved.
6. Identifying and obtaining relevant datasets while looking at a business problem.
7. Installing and managing Big Data processing environments based on Hadoop or MongoDB at a departmental level.

Syllabus:

1. Big Data Introduction

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

2. Big Data Technology - Overview

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

3. Big Data - Privacy & Ethics

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

4. Sources for Big Data

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

5. 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

6. Public Data Sources

• Introduction
• Weather
• Economics
• Finance
• Regulatory Bodies

7. Data Mining - Concepts and Tools

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

8. Big Data Technologies - Hadoop

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

9. Data Processing with Hadoop

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

10. 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

11. Document Databases

• Introduction
• Documents
• Document Design Considerations
• Fields

12. Data Modelling with Document Databases

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

Eligibility:

You are eligible for Big Data Foundation training and certification course if you are working in any of the following fields:

• Software Engineers
• Application Developers
• Marketing Experts
• Finance Specialists
• IT Architects
• System Administrators
• Technical Recruiters
• Business Analysts
• Technical Support Specialists

Prerequisites:

There are no formal prerequisites for the exam, but the basic knowledge of Hadoop and Mongo DB will be helpful for participants to understand the concepts.

Big Data Training Delivery Style:

This Big Data Foundation Training focuses on experiential learning. The material of this course is divided into 60-90 minutes of interactive sessions.

Not only this, if you are participating, expect yourself to get indulged with interesting group activities. By this, you will get a chance to put the theory into action.

This training will be nothing like any ordinary training you imagine. We follow a vast range of creative methodology which will allow you to wrack your grey matter and boost your energy up to participate. 

The key features of our training program would be:

• Training sessions in a storytelling format
• Exhibition of concepts with the help of professional examples
• Self-analysis and group discussions
• Case studies as the application of the concepts which were taught
• Vibrant presentations along with individual and team activities
• Post-training reading suggestions

Benefits of Big Data Training

• Get hired easily.
• Prove your Big Data skills & understanding.
• Gain an in-depth understanding of Big Data & its implementation.
• Implement your skills in any Big Data applications.
• Get Acknowledged as a Big Data Professional worldwide.

Examination Format

The Big Data Foundation certification is governed, administered, and maintained by GSDC. The Big Data Foundation Certificate will be the pre-requisite for future Big Data Foundation certification courses.

Exam Format - Objective Type, Multiple Choice

Exam Duration - 1 hour

No. of Questions - 40 (multiple-choice questions)

Passing Criteria - 26 out of 40 (65% is needed to pass)

• 60-minutes exam.
• 40-multiple choice questions (MCQ).
• 26 out of 40-65% is needed to pass.
• Certificate – Within 5 business days
• Result - Immediately after the exam
• Closed book

In case the participant does not score the passing percentage, they will be allowed to take the 2nd attempt at no additional cost. Re-examination can be taken up to 30 days from the date of the 1st exam attempt.

Faculty:

Big Data Foundation training will be delivered by accredited trainers. The instructors for this course are highly experienced professionals with 16+ years of industry experience and have trained more than 7000 professionals

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