Big Data Overview 1 Day Training in Krakow

Big Data Overview 1 Day Training in Krakow

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From zł2,377.07


Regus - Krakow, Fronton

Budynek Fronton ul, Kamienna 21, 31-403 Kraków, Poland

31-403 Krakow


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Refunds up to 7 days before event

Our classroom training provides you the opportunity to interact with instructors and benefit from face-to-face instruction.

About this event

Course Description:

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.

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

Target Audience:

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 Objectives:

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.

Course Agenda:

Day 1

Big Data Fundamentals

Big Data Sources

Data Mining: Concepts and Tools

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