Data Analytics Journey Phase 2

Why a Modern Data Platform is needed?

• Gain Clear Visibility and made available to everyone (Single Source of Truth)
• Make your data infrastructures modularization (Flexible & Scalable)
• Highly customizable insightful data visualization (Dashboard that speeds up decisions)
• Acts as DaaS (Data-as-a-Service), should transparently orchestrate and automate the lifecycle, copy management, compliance, and governance of data across infrastructures, application types, formats, containers, locations, even SaaS.
• Collection of data via real-time data sources in addition to batch loads.
• Data can be generated from internal systems, cloud-based systems, along with any external data that is provided by partners and third parties.
• Providing analytics to traditional platforms such as data marts along with specialty databases such as graphing and mapping.
• Support for all types of users ranging from customers to data scientists.

Leading Edge Modern Data Platform Architecture

Compatibility, Performance, Scalability, and Cost-effectiveness are carefully considered in the data platform design, we also well-used AI (Artificial Intelligence) and ML (Machine-learning) technologies to enhance the operational efficiency and insight discovery capability.

Compatibility

Such as:

• Supports different Data Sources
• Supports different Data Formats
• Supports different Usages
• Supports different Tools/Platforms Integration

Performance

Such as:

• Speed
• Support
• Functionality
• Reliability
• Reusability

Scalability

Such as:

• Supports new Data Sources
• Supports new Data Formats
• Supports new Usages
• Integrates with new Systems

Cost-effectiveness

Such as:

• Low Running Cost (Subscription-based, Pay as you go!)
• Low Maintenance Cost (Minimized the local hardware/software, less maintenance resource required)
• Low Future Expand Cost (Most changes/upgrades are on the cloud, minimized equipment and software license cost)