证券日报网讯 TCL科技（000100）8月22日在互动平台回答投资者提问时表示，随着数据可视化需求激 增，推动显示面板作为交互载体的价值不断提升。 ...

Core Insights - The increasing importance of data in enhancing business decision-making efficiency is driving banks to explore data middle platform and visualization services [2][3] - The implementation of data visualization services at Industrial Bank has significantly improved data analysis across various business lines, breaking down data silos and enhancing data sharing and reuse [2][4] - The shift from traditional reporting to data storytelling is essential for banks to optimize decision-making processes and operational efficiency [5][6] Group 1: Data Visualization Services - Industrial Bank has successfully implemented data visualization services across multiple business lines, including retail, corporate finance, interbank and financial markets, and risk management [2][3] - The introduction of data visualization services has addressed two major bottlenecks in data reporting: the timeliness of data and the rigidity of report formats, allowing for faster and more customized data presentations [2][4] - A total of 44 branches and 20 business departments at the headquarters are currently utilizing the enterprise-level data visualization services [6] Group 2: Challenges and Solutions - Many banks have faced challenges such as redundant construction of data reporting platforms at branch levels, distributed work models hindering data integration, and complex data usage permissions [3][4] - To overcome these challenges, banks are increasingly building enterprise-level standardized data middle platforms to integrate and manage data across branches [3][4] - The need for a shift from traditional fixed reporting to intelligent, story-driven data visualization is emphasized to enhance collaboration and decision-making efficiency [5][6] Group 3: AI Integration - The integration of AI technology with data visualization services is seen as a new challenge for banks in their digital transformation journey [7][9] - AI can assist in the entire data visualization process, lowering barriers to data usage and improving analysis and decision-making efficiency [7][8] - Banks are encouraged to develop Data Agents that combine business problem-solving capabilities with decision-making execution abilities to enhance the effectiveness of AI in data applications [8][9] Group 4: Compliance and Ethical Considerations - The development and application of data intelligence agents must prioritize compliance with data security, algorithm transparency, fairness, and system stability [10] - Addressing issues such as data leakage, misuse, and ethical concerns is crucial to ensure that data intelligence agents are both safe and efficient [10]

数据可视化驾驶舱是数据驾驶舱不可或缺的重要组成部分。它运用先进的可视化技术，将原本枯燥乏味 的数据转化为生动形象的图形与动画，使决策者能够更直观地洞察数据背后的深层含义。无论是常见的 柱状图、折线图，还是更具表现力的散点图、热力图，数据可视化驾驶舱都能依据具体需求，以最恰当 的方式呈现数据。这种直观的数据展示方式，不仅大幅提升了决策者的阅读效率，更有效降低了因数据 误解而导致的决策失误风险。 在当今数字化浪潮中，企业面临着海量数据处理的挑战，如何从纷繁复杂的数据中精准提取有价值信 息，以支撑快速且准确的决策，成为企业生存与发展的关键命题。在此背景下，数据驾驶舱作为数据可 视化与数据分析的高级形态，正逐渐崭露头角，成为企业决策的新引擎。 数据驾驶舱，从名称便可直观理解其核心价值，它如同汽车的驾驶室，为决策者打造了一个全面且直观 的数据展示平台。这一平台整合了数据收集、处理、分析以及展示等多个关键环节，将原本晦涩难懂的 数据巧妙转化为简洁明了的图表与图像。决策者借助数据驾驶舱，能够实时掌握企业的各项关键指标， 像销售额、客户满意度、生产效率等，从而及时察觉潜在问题，并迅速做出针对性调整，确保企业运营 始终处于高效 ...

Core Insights - The company has launched a retail credit data visualization service to enhance data readability and value extraction [1][2] - The initiative aims to overcome the challenges of data fragmentation and low timeliness, enabling business personnel to access effective data quickly [1] - The service utilizes advanced technologies such as stream computing and dynamic visualization to provide real-time data support for business decision-making [1] Group 1: Data Integration and Efficiency - Prior to the new service, data development required traditional methods involving lengthy delivery cycles by R&D personnel [2] - The new drag-and-drop self-service feature allows business personnel to directly engage with data, significantly improving efficiency and automation [2] - The service has built nearly a thousand dimensional indicators and achieved nearly 200,000 access visits, with mobile engagement leading among departments [2] Group 2: Future Development - The company plans to continue optimizing the retail credit data visualization service in collaboration with its data management department [2] - The focus will be on enhancing the user experience and providing more efficient and agile services in the retail credit business domain [2]

Core Insights - Data visualization has become a core skill for businesses and individuals to interpret information and identify trends in the era of big data. The article reviews over 30 mainstream data visualization tools across seven categories to help match business needs accurately. Group 1: Business Intelligence (BI) Tools - Tableau is a leading BI platform offering a complete solution from data connection to advanced analytics, with a unique VizQL technology that optimizes visualization logic. Walmart saved millions in inventory costs using Tableau [1] - Microsoft Power BI integrates deeply with Office 365, providing advanced features at a subscription price of $9.9 per month. A retail company reduced sales report generation time from 3 days to real-time updates using Power BI [1] - Qlik Sense utilizes in-memory computing to perform data association analysis in 10 seconds, improving fraud detection accuracy by 40% for a bank [1] Group 2: Programming Visualization Libraries - Matplotlib, a standard Python library, supports over 50 basic chart types but requires extensive coding for customization [2] - D3.js allows pixel-level control through data binding with DOM elements, used by GitHub for rendering code submission heatmaps, though it has a steep learning curve [2] - Plotly, based on React, supports complex visualizations like 3D surfaces and is used by a meteorological agency for dynamic typhoon path analysis [2] Group 3: Online Visualization Platforms - Google Data Studio integrates seamlessly with Google services, allowing real-time collaboration for up to 20 users, enhancing reporting efficiency by 70% for a marketing agency [4] - Infogram offers over 200 magazine-quality templates, increasing donation conversion rates by 25% for an NGO [4] - Flourish is used by The New York Times for creating animated election maps, although exporting dynamic charts can be costly [4] Group 4: Open Source Tools - Apache Superset, an open-source solution from Airbnb, supports real-time freight monitoring systems but requires a professional operations team for cluster deployment [6] - Metabase allows business users to generate reports without SQL knowledge, improving response times for an e-commerce customer service team by three times [6] - Redash connects to over 200 data sources and allows for custom plugin development, but requires self-hosting with associated hardware costs [6] Group 5: Specialized Tools - ArcGIS supports geospatial analysis and was used by a city planning bureau to optimize traffic light configurations [8] - Ruanqian BI offers open-source front-end pages for customization and integration into Java applications [8] - RAWGraphs specializes in complex visualizations for multi-variable data, used by a gene research institution to identify potential targets [8] Group 6: Emerging Intelligent Tools - Observe.AI integrates GPT-4 to automatically generate analysis reports from data tables, significantly reducing report preparation time [9] - Airtable combines spreadsheet and database functionalities, helping product teams manage development timelines effectively [9] Group 7: Tool Selection Decision Matrix - The article suggests evaluating tools based on technical capability, interaction needs, data scale, and collaboration requirements, providing examples for different types of organizations [11]