Kompetensi

Data Science

Systematic Approach to Data Analytics

Big data analytic is a long-term journey for organizations to achieve desired business objective. Nowadays, enterprises 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 adapt at predicting the future.

Course Objective

1. Merangsang idea dan mengenal pasti aplikasi BDA yang berimpak tinggi dalam organisasi masing-masing.
2. Merangsang idea bilakah dan bagaimanakah bermula pembangunan aplikasi BDA.

Course Outcomes

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

Course Outline

1. BDA Overview
   • 3 Elements – Data Source, Advanced Analytics & Data Presentation
   • Involves Technological Framework for Enablement
   • Success Cases around the World
   • Modern Data Scientist skillsets
   • CRISP-DM
2. 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 to Descriptive Analytics
   • Diagnostics Techniques
3. Important Considerations in Building BDA Applications
   • Business Aspects
   • Domain Knowledge
   • Data Understanding
   • Determine Measurable Output (ROI)
   • Technical Aspects
   • Key Competency Areas
   • ICT Infrastructure
   • Big Data Technologies
   • Hadoop
   • Advanced Analytics
   • Web/Social Media Mining
4. 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