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Course Outline

Introduction

Data management involves the storage and processing of information. Within an enterprise context, this process becomes significantly more complex. The volume of data, along with the speed at which it must be processed, secured, shared, and analyzed, is critical to success.

This course is designed for entry-level engineers. It explores the various technologies, tools, architectures, and design methodologies employed to manage large volumes of data. We cover traditional data storage methods, such as relational databases, as well as newer, less structured approaches.

Traditional file systems are compared to distributed file systems, and traditional server architecture is compared to clustered server architecture, all within the context of managing and processing big data across distributed systems.

Attendees will conduct hands-on exercises and tests, followed by coaching from the instructor and group discussions.

Key topics include:

Hadoop

MS SQL

Oracle

Exadata

Data hub

NoSQL

NewSQL

Storage

Business Intelligence

Data Architecture

Requirements

  • Fundamental understanding of databases
  • Some background in programming
 35 Hours

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Price per participant

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