VIVIDATA Business Intelligence

VIVIDATA Business Intelligence

Unlock actionable insights from your big data with our easy-to-use, end-to-end analytics platform.

Unlock actionable insights from your big data with our easy-to-use, end-to-end analytics platform.

Partner solution Public cloud/HCSO/HCS

Accelerate Your Digital Transformation, Get Ahead of the Competition

Accelerate Your Digital Transformation, Get Ahead of the Competition

Unleash Data Value: Make Informed Decisions, Reduce Costs, and Improve Efficiency

Unleash Data Value: Make Informed Decisions, Reduce Costs, and Improve Efficiency

Zero Code

Fast deployment, application, and iteration; simple operations; automated data processing; visualized analysis; and service-oriented data system

Ease of Use

End-to-end self-service operations—from data connections and processing to analysis and display—are achieved through simple drag-and-drop.

Secure and Reliable Enterprise-Level Management System

More flexible row- and column-level permission management policies, seamless integration with your identity management system through LDAP, and brute-force attack defense to protect your passwords

Harness Data Value: Make Smarter Decisions

Harness Data Value: Make Smarter Decisions

Scenario

Sales and Operations Analysis

Production Efficiency Analysis

Customer Analysis

Financial Management Analysis

Challenges
  1. Sales and marketing success hinges on an in-depth analysis of customer, product, and market data.
  1. The volume and complexity of production data make it difficult to accurately predict device failures.
  1. Customer data is fragmented across platforms and departments, preventing real-time analysis and reducing your ability to respond quickly.
  1. Inconsistent formats and standards from disparate financial data sources create integration barriers and undermine data reliability.
Solution
  1. Monitor and adjust sales and marketing data with real-time data processing.
  2. Optimize your strategies, with analytics and machine learning algorithms for sales forecasting and marketing evaluation.
  1. Machine learning algorithms predict device faults using historical data and real-time monitoring, enabling proactive repairs and reducing unplanned downtime.
  2. AI algorithms continuously optimize production plans, scheduling, and resource allocation to maximize production efficiency and output.
  1. Unify scattered customer data onto a single platform, standardizing formats to ensure data consistency and integrity.
  2. Real-time data processing lets you analyze and monitor customer data continuously—so you stay aligned with their needs and instantly adjust strategies.
  1. Integrate financial data from all sources into a unified platform to ensure consistency and accuracy.
  2. Predictive analytics and real-time data processing is then applied to build financial forecasting models, enabling real-time monitoring and feedback.
Benefits
  1. Uncover deeper insights into customers' preferences, sales trends, and market demands.
  2. Accelerate decision-making and adjust strategies.
  3. Optimize resource allocation, reduce costs, and maximize return on investment (ROI).
  1. Boost production efficiency and equipment utilization while reducing maintenance costs and energy consumption.
  2. Achieve consistent, high-quality products.
  3. Improve production efficiency and shorten the production cycles.
  1. Better understand customer needs, behavior, and preferences, and predict trends.
  2. Deliver exceptional customer experiences that build brand loyalty.
  3. Improve marketing ROI.
  1. Reduce financial risks.
  2. Optimize resource allocation, reduce operating costs, and improve efficiency.
  3. Anticipate future trends to shape long-term strategic planning and strengthen your competitive positioning.

Sales and Operations Analysis

Challenges
  1. Sales and marketing success hinges on an in-depth analysis of customer, product, and market data.
Solution
  1. Monitor and adjust sales and marketing data with real-time data processing.
  2. Optimize your strategies, with analytics and machine learning algorithms for sales forecasting and marketing evaluation.
Benefits
  1. Uncover deeper insights into customers' preferences, sales trends, and market demands.
  2. Accelerate decision-making and adjust strategies.
  3. Optimize resource allocation, reduce costs, and maximize return on investment (ROI).

Production Efficiency Analysis

Challenges
  1. The volume and complexity of production data make it difficult to accurately predict device failures.
Solution
  1. Machine learning algorithms predict device faults using historical data and real-time monitoring, enabling proactive repairs and reducing unplanned downtime.
  2. AI algorithms continuously optimize production plans, scheduling, and resource allocation to maximize production efficiency and output.
Benefits
  1. Boost production efficiency and equipment utilization while reducing maintenance costs and energy consumption.
  2. Achieve consistent, high-quality products.
  3. Improve production efficiency and shorten the production cycles.

Customer Analysis

Challenges
  1. Customer data is fragmented across platforms and departments, preventing real-time analysis and reducing your ability to respond quickly.
Solution
  1. Unify scattered customer data onto a single platform, standardizing formats to ensure data consistency and integrity.
  2. Real-time data processing lets you analyze and monitor customer data continuously—so you stay aligned with their needs and instantly adjust strategies.
Benefits
  1. Better understand customer needs, behavior, and preferences, and predict trends.
  2. Deliver exceptional customer experiences that build brand loyalty.
  3. Improve marketing ROI.

Financial Management Analysis

Challenges
  1. Inconsistent formats and standards from disparate financial data sources create integration barriers and undermine data reliability.
Solution
  1. Integrate financial data from all sources into a unified platform to ensure consistency and accuracy.
  2. Predictive analytics and real-time data processing is then applied to build financial forecasting models, enabling real-time monitoring and feedback.
Benefits
  1. Reduce financial risks.
  2. Optimize resource allocation, reduce operating costs, and improve efficiency.
  3. Anticipate future trends to shape long-term strategic planning and strengthen your competitive positioning.

Go Intelligent with an End-to-End Solution

Go Intelligent with an End-to-End Solution

Data Platform

Data lifecycle management platform that covers collection, storage, computation, management, and consumption

Deployment on Huawei Cloud or Huawei Cloud Stack, or lightweight deployment

Data Processing & Analysis

Import and analysis of gigabytes to petabytes of multimodal data in real time through massive amounts of computing resources

Offline, semi-online, and online scaling to meet any business requirement

Data Application
Power industry-specific operations with data applications refined by proven experience from 10,000+ global customers.

Digital applications for diverse industries through KooGallery, an online store jointly operated by Huawei and its partners

Data applications for R&D, production, supply chain, sales, and service operations

New applications such as large-screen dashboards and intelligent reconstruction of legacy applications

Continuously Innovate Alongside Millions of Customers

Continuously Innovate Alongside Millions of Customers

Join Leading Industry Partners to Accelerate Development

Join Leading Industry Partners to Accelerate Development

VIVIDATA

VIVIDATA is an AI vendor that focuses on data technologies. It is committed to building world-leading data intelligence solutions.

  • VIVIDATA

    VIVIDATA is an AI vendor that focuses on data technologies. It is committed to building world-leading data intelligence solutions.

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