Phase 1 – Data Consultation

• Define business objectives and KPIs
• On-prem to Cloud Solution
• Centralize Cloud Architecture Design
• Guidelines on industries’ best practice
• Data governance and security advisory
• Various database optimization solution

Keyword: Data Study, Architecture, Roadmap

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Phase 2 – Modern Data Platform

• Ready to go from on-prem data system to cloud lakehouse architecture data platform?
• Data sources are ready for cloud integration?
• Data models are ready for dynamic data visualization enhancement?
• Data governance and PII security implemented?
• Cloud optimization such as parallel process?
• Faster data access such as streaming data for application?
• Ready to use for machine learning projects?

Keyword: Data Platform, Modelling, Security, Analysis

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Phase 3 – Machine Learning

• Understand the business problem or objective
• Data collection and preparation
• ML model selection
• Model training
• Model validation
• Model deployment

Keyword: Scoring System, Customer Segmentation

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Phase 4 – Prioritization of new Data Project

• Prioritizing the project enhancement requests from different business users
• Reviewing data project results and handling new initiative or enhancement
• Rerun the cycle phase 1 to 3 for reading out scope of work

Keyword: Prioritization, Scope of Work

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