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Big Data for Management and Professionals

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The digitisation of data, the availability of sensors, and the affordability of data storage have given rise to the rapid production of humongous pool of data. The lack of knowledge and talents on how to tap the use of these data for innovative and productive solutions to solve business problems have prevented organizations from taking advantage of data-driven opportunities and accelerate data-analysis transformation. Organizations must prepare themselves to be “data-driven” business in this Big Data era. This course empowers you with the skills and confidence in managing and implementing Big Data solutions to take advantage of the tremendous value arising from the data reservoir. Through lectures, case studies, discussions and hands-on practicum, you will be able to describe the Big Data landscape, determine what a Big Data problem and solution is, get value out of Big Data, describe the type of database for Big Data storage, and explain the architectural components and programming models for scalable Big Data Analytics.


Learning Objectives and Outcomes

Course will enable participants to:
1. Define Big Data and describe the rise of Big Data landscape.
2. Learn how to make strategic use of Big Data available in organizations.
3. Understand the role of databases in Big Data Analytics.
4. Understand how Big Data Analytics can help organizations achieve a competitive advantage.
5. Appreciate the benefits and insights that Big Data Analytics bring to the organizations.
6. Understand the 5-step process to structure Big Data Analytics.
7. Describe the architectural components and programming models for scalable Big Data Analytics.

Teaching methodology: Lectures, Case Studies, Discussions, Practicum

Course Contents

Big Data

  • What is Big Data?
  • The growth of Big data and the Internet of Things
  • Data-driven organization

Strategic use of Big Data

  • Using Big Data to improve decision making
  • Using Big Data to drive operational improvement
  • Using Big Data as business asset
  • Making a business case for Big Data

Turning Big Data into insights

  • What is Big Data Analytics?
  • Understanding the different types of data
  • Understanding the different types of Big Data Analytics
  • Combining analytics for maximum success

Big Data databases

  • Traditional databases and its limitations for Big Data
  • The rise of NoSQL (Not Only SQL) databases
  • Introducing MongoDB

Big Data Analytics Process

  • The 5-step process to structuring Big Data Analytics
  • Data visualisation
  • Practicum: Case study on Big Data Analytics

Big Data Architecture and Programming Models

  • Hadoop
  • YARN resource and job management system
  • Hadoop Distributed File System (HDFS)
  • MapReduce programming model
  • Practicum: Hadoop


Who should attend?

  • Administrators and managers
  • Any professionals who are new to Data Science and are interested to learn Big Data, Big Data strategy, Big Data Analytics, Big Data databases, and Big Data architecture and programming models.

Course Duration: 3 days

Course Fees : $2400 + GST

Course Leader

Associate Professor Danny Poo

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