Big Data Technology Trends & Insights Training

Start Date End Date Venue Fees (US $)
19 Jul 2026 Kuala Lumpur, Malaysia $ 4,500 Register
06 Dec 2026 Jeddah, KSA $ 4,500 Register

Big Data Technology Trends & Insights Training

Introduction

People and industries are constantly surrounded by data. This data comes in different forms and sizes, but it is omnipresent, and it is growing in size day by day, as well as in its possible applications and technology developments. The recognition of trends and insights into new technologies and developments ensures growth and sustainability. This training course provides comprehensive information on a full set of Big Data technology characteristics, and trends as well as analysis techniques and software used to analyse Big Data. The ability to extract, model, and analyze information is now possible even with the technologies and software which is freely available in the market. Big Data Analytics can assist organizations in identifying trends and adjusting operational procedures to improve the results, to increase revenue and client experience. This Big Data Technology Trends & Insights Training course will provide a practitioner approach to identifying requirements for the application of data science, how these can be adopted, technologies available, which analytical models may be appropriate to provide valuable data, and how to make sense of Big Data and Analytics.

This training course will feature:

  • An Overview of Big Data Technologies
  • Adaptation and Approach of Lifecycles and Models with the New Trends
  • Methods and Models for Acquiring Insights into Big Data
  • Advanced Methods and Models for Big Data Analytics and Trends
  • How to Select Appropriate Tools
  • Case studies of Big Data use.

Objectives

    By the end of this training course, participants will be able to:

    • Understand the potential of Big Data for their organization
    • Appreciate trends within the Big Data technology development
    • Consider How to gather appropriate Insights from the data
    • Learn from case study examples and use case scenarios
    • How to successfully achieve results from applying best practices

Training Methodology

The training course will combine direct discussion of topics, with presentations and interactive practical exercises, supported by video materials, activities, and case studies. Delegates will be introduced to the world where computers and machines are trained to behave in the manner of humans and to help humans make optimal decisions. This training course will utilize a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. This includes a theoretical presentation of the concepts. Delivery will be by presentation, group syndicate exercises, training e-manual and interactive seminars, as well as a group discussion on the results of the exercises.

Who Should Attend?

This training course has been designed for all those involved in the technology, research and statistical analysis of corporate data.

  • CEOs
  • CTOs, CIOs
  • Web designers
  • Application designers
  • Product designers
  • Marketing and research specialists
  • Statistical and Research Analysts
  • Key Application Development and Data Research Personnel
  • Technology Engineers, Telecommunication engineers

Course Outline

Day 1 : Big Data Technology Introduction

  • Current Practices and level of technological development
  • Big data as a new reality
  • Analytical Architecture for Big Data Technologies
  • Roles for Big Data within the Technology
  • Key Drivers for Big Data Analytics Technology Development
  • Case Study and Summary

Day 2 : Data Analytics Models and Insights

  • Data Analytics Lifecycle
    • Stage 1 - Discovery
    • Stage 2 - Preparation of Data
    • Stage 3 - Model Planning and Review
    • Stage 4 - Model Creation
    • Stage 5 - Communication Plan
    • Stage 6 - From Planning to Operation
  • Use of models for gathering insights into the data
  • Exercise: Use of big data analytics for trend identification 

Day 3 : Big Data Technologies in use

  • Communications technologies
  • Cloud computing
  • Security and Privacy issues
  • Continuous innovation
  • The concepts of data lakes

Day 4 : Big Data use cases

  • Data visualisation tools
  • Ensuring data quality with AI
  • Big data Ingestion
  • Big Data processing
  • Big Data analytics for Business Intelligence

Day 5 : Big Data future

  • Data science projects
  • Self-serving data analytics
  • Best in class examples
  • Failures of crypto currencies (myths vs. reality)
  • Risk mitigation within Big Data

Accreditation

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