This is an awareness course designed to provide you with an understanding of Big Data, the potential sources of Big Data that can be used for solving real business problems. The course also introduces Big Data technologies, such as Hadoop and MongoDB, and provides the overview of data mining and the tools used in it.

Classroom
  • April 28th 2023
  • 9 am – 5 pm
  • Regus, Guelph
  • Price: C$545.00

Duration                                Learning Credits

1 day-8 hours of                    8 PDU’s

Session   


Public Classroom Pricing:    

Early Bird Price: CAD 649.00

Regular Price: CAD 799.00


Instructor-Led Virtual Live Pricing:

Early Bird Price: CAD 549.00

Regular Price: CAD 699.00


Private Group / In-House Learning:

Have a group of 5 or more people? 

Register yourself with a special pricing and

request the training exclusively

  • 4.5 | 2546 Ratings | 5246 Attended |245 Corporate Trainings
Course Outline

Module 1: Big Data Fundamentals

● Big Data: History, Overview, and Characteristics

● Big Data Technologies: Overview

● Big Data: Privacy and Ethics

● Big Data Projects

● Big Data Success Stories

Module 2: Big Data Sources

● Enterprise Data Sources

● Social Media Data Sources

● Public Data Sources

Module 3: Data Mining: Concepts and Tools

● Data Mining: Introduction

● Data Mining Tools

Who can attend?

This course is best suited to information technology professionals who possess intermediate to advanced programming, system administration, or relational database skills and are looking to move into the area of Big Data. These include:

● Software Engineers

● Application Developers

● IT Architects

● System Administrators

The course can also be of benefit to other professionals, such as Business Analytics and Research Analytics, who possess strong Information Technology skills and have a deep interest in Big Data analytics and the benefits it can bring to an organization.

Learning Goals

● Explain Big Data and its characteristics.

● Explain the most popular tools/technologies for Big Data processing.

● Identify various types of enterprise, social media, and public data sources.

● Explain data mining and popular tools used for data mining.

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