Modern Data Platform

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 and cost saving in one off and on going support (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.
  • Support for all types of users ranging from customers to data scientists.
  • Ready to support Machine Learning.
Leading Edge Modern Data Platform 領越集團現代化數據平台

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.



Such as:

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



Such as:

  • Speed
  • Support
  • Functionality
  • Reliability
  • Reusability



Such as:

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



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)

Example usages of Modern Data Platform:

Retail Market

  • KPI Summary: A KPI summary can be used to track key performance indicators such as revenue, conversion rates, average order value, and other metrics. This analysis can help retailers identify trends and areas for improvement in their business.
  • Sales Analysis: Sales analysis can help retailers understand which products are selling well and which are not. This information can be used to optimize pricing, inventory management, and product selection.
  • In-App / Web Journey: Analyzing the in-app or web journey of customers can help retailers identify pain points in the customer experience and optimize their user interface and design to improve conversions.
  • Bounce Rate Analysis: Bounce rate analysis can help retailers understand why customers are leaving their site without making a purchase. This information can be used to identify areas for improvement in website design, content, and overall user experience.
  • Conversion Rate Analysis: Conversion rate analysis can help retailers understand how many visitors are converting into customers, and which factors are influencing their decision to make a purchase. This information can be used to optimize pricing, promotions, and website design to increase conversions.
  • Channel / Deep Link Analysis: Channel and deep link analysis can help retailers understand which marketing channels and campaigns are driving the most traffic and revenue to their websites. This information can be used to optimize marketing spend and improve ROI.
  • Campaign Analysis: Campaign analysis can help retailers understand which marketing campaigns are most effective at driving traffic and sales. This information can be used to optimize marketing spend and improve ROI.
  • Download Analysis: Download analysis can help retailers understand how many customers are downloading their mobile app and how they are using it. This information can be used to optimize the app design and user experience to improve engagement and conversions.


Logistics Industry

  • Revenue Analysis: Analyzing revenue by service type, customer, and region to identify trends and opportunities for growth.
  • Volume Analysis: Analyzing shipment / freight volume by service type, customer, and region to track demand and optimize resources.
  • Carrier Performance: Analyzing carrier performance data to track on-time deliveries, shipment damages, and other metrics to ensure the quality of service provided by the carriers.
  • Freight Cost Analysis: Analyzing transportation and logistics costs to identify cost-saving opportunities and improve profitability.
  • Shipment Tracking: Analytics on the shipment status, reducing shipment delays, and improving customer satisfaction.
  • Supply Chain Visibility: Providing customers with end-to-end visibility into their supply chain, including inventory levels, shipment status, and transportation details.
  • Route Optimization: Analyzing historical transportation data and traffic patterns to optimize delivery routes and minimize transportation costs.
  • Customer Segmentation: Analyzing customer data to segment customers based on their shipping preferences, order frequency, and other factors to tailor services and marketing efforts to meet their needs.
  • Risk Management: Analyzing data on weather patterns, natural disasters, and other risks to proactively manage risks and mitigate potential disruptions in the supply chain.
  • Warehouse Efficiency: Analyzing warehouse data to optimize warehouse layouts, reduce processing times, and improve productivity.
  • Sustainability Analysis: Analyzing data on carbon emissions, fuel consumption, and other sustainability metrics to identify opportunities to reduce environmental impact and improve sustainability in the supply chain.
  • Custom Clearance Efficiency: Analyzing data on custom clearance processes to optimize efficiency and reduce lead times.
  • Insurance Claims Analysis: Analyzing data on insurance claims to identify trends and opportunities for improvement in the insurance process.


Social Analytics

  • Sentiment Analysis
  • Profile Monitoring
  • Post Distribution
  • Keyword Menu


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Should you have any question or interest to check out more details, welcome to contact us.

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