Overview

With the continuous advancement of enterprise informatization construction, a large amount of business data has been generated. How to awaken the "dormant" business data and improve data analysis capabilities has become a business pain point for enterprises.

The auxiliary decision analysis system, through in-depth mining of massive data in oil sales enterprises, supports comprehensive decision analysis from top to bottom, supports multi-dimensional queries, provides fixed and customized reports, meets different report needs of customers, adopts mature prediction models to predict and analyze sales situations, effectively analyzes customer churn based on customer consumption, comprehensively displays the completion status of key KPI indicators, and achieves scientific auxiliary analysis and decision-making.

function

• Diversified reporting modes:The system provides two modes of reports: fixed reports and flexible reports.
  Fixed reports mainly solidify the reports frequently used in the company's daily work, reduce the process of configuring parameters for business personnel, and improve the efficiency of daily report work for business personnel.
  Flexible reports are mainly designed for report applications in special scenarios, providing business personnel with flexible and powerful customized report tools that can quickly generate a variety of rich and diverse charts. At the same time, it supports rapid exploration and ad hoc queries of massive business data, discovering potential business information and statistical patterns.
• Scientific sales forecast:Based on a comprehensive analysis of historical sales data and objective influencing factors, combined with appropriate mathematical models, multi-level sales forecasting has been achieved. Through the system, comprehensive prediction queries, plan achievement warnings, and sales anomaly analysis have been carried out.
• Effective customer churn analysis:Based on the business characteristics of oil sales enterprises, through in-depth analysis and mining of customer behavior related data, a customer churn model is established to comprehensively evaluate customer churn tendencies and provide data basis for enterprises to regain customers.
• Diversified business analysis:Conduct multidimensional, all-round, and multi-dimensional analysis of the overall business and various business processes such as procurement, distribution, warehousing, and sales in different regions, at different times, and at different organizational levels.
• Visual comprehensive display:Comprehensive visualization display of key KPI indicators for enterprise operations, supporting data navigation downwards according to different organizational structures and regions, and supporting various display methods such as desktop and large screens.

feature

• Combining data warehousing with distributed data processing and in memory data processing technologies, possessing the ability to design and process massive amounts of analytical data;
• Targeting analysis, mining, prediction, and decision-making, supporting multiple models and algorithms, and can be integrated with advanced optimization tools to achieve the practical application of advanced business intelligence;
• Through mechanisms such as messages, processes, and services, statistical analysis and data mining are integrated into management, decision-making, and business operations;
• Adopting RIA, FLEX, and HTML5, it supports advanced display implementation capabilities for large screens, tablets, and mobile phones;
• Efficient decision support development framework closely integrated with mainstream commercial BI products;
• Provide fixed and flexible reports, supporting multiple dimensions;
• Query and ad hoc query, supporting data drilling.