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Course Objectives

This course is suggested for business professionals involved in strategic planning. Nowadays, enterprise are using data strategically to help them become more competitive, increase revenue and profits, reduce risk and begin new initiatives or even to deliver exceptional products and services. Thus, advanced analytics enable us to become more adept at predicting the future.

What Will You Learn?

  • Stimulate ideas and identify potential high-impact applications in their respective organizations;
  • Answer the ‘when, and how to start building BDA application’ question.

Target Audience

This course is suggested for individuals who keen to understand big data ecosystem, all users, IT, Management and etc.

Training Outline

BDA overview
  • 3 elements: data source, advanced analytics & data presentation
  • Involves technological framework for enablement
  • Success cases from around the world
  • Modern Data Scientist skillsets
Importance of advanced analytics vs. traditional BI
  • Huge amount of information captured in unstructured data – sentiments from social media is a good example
  • Predictive & prescriptive analytics, in addition of descriptive diagnostics techniques
Important considerations in building BDA applications
  • Business aspects.
    • Domain knowledge
    • Data understanding
    • Determine the measurable output (ROI)
  • Technical aspects
  • Key competency areas
  • ICT infrastructure
  • Big data technologies – Hadoop, advanced analytics, web/social-media mining
The recommended approach to start a BDA project
  • Identify business cases with tangible ROI
  • Prioritize by communicating with different departments
  • Feasibility study
  • Pilot projects
  • Build competency
  • Plan for future implementation/scaling
  • Raise example use cases
Group activity – brainstorming and facilitating the development of ideas
  • Highly interactive session
  • 4 to 5 people in a group, identify potential business cases based on domain knowledge
  • Simulate a project team environment
  • Guide participants through the step-by-step process via templates:
    • What are the theoretical benefits of implementing such initiative for the organization?
    • How critical is the identified issue?
    • What will happen if problem not solved?
    • What are the available data?
    • Understanding the data on-hand
    • Is there a need to collect more data? How easy/difficult is that?
    • Potential ROI
    • Start small with pilot projects