Data Agent - Volcano Engine's Next Generation Enterprise Data Intelligence Body

What is Data Agent?

Data Agent is a new generation of enterprise-level data intelligence from Volcano Engine, focusing on data analytics and smart marketing.Data Agent integrates structured and unstructured data within the enterprise, and generates comprehensive and in-depth research reports based on in-depth research and analysis, covering the current status of the data to help enterprises better understand market dynamics and customer needs. The reports cover the current status of data, provide valuable insights and recommendations, and help companies better understand market dynamics and customer needs. data Agent is proficient in a variety of data analysis tools, and can automate the generation of complex reports, greatly improving work efficiency. data Agent provides intelligent conversation assistance functions, helping sales staff to more accurately grasp the needs of the customer in the communication with the customer, and improve the conversion rate and customer satisfaction. data Agent provides intelligent conversation assistance functions, helping sales staff to more accurately grasp the needs of the customer, and improve the conversion rate and customer satisfaction. Data Agent's goal is to optimize enterprise data management and marketing activities based on intelligent means, improve business efficiency and effectiveness, and become the first AI expert of enterprise data team.

Main functions of Data Agent

• intelligent analysis (religion)::
  • Flexible Configuration: Customize the data model and analysis process according to business needs to meet the personalized needs of different scenarios.
  • conversational query: Fast access to data insights based on natural language interaction without complex operations.
  • multimodal analysis: Combine multiple types of data such as text, images, and video for in-depth analysis to provide a comprehensive view.
• Proactive Insights and Actions::
  • deep contextual understanding: Accurately understand enterprise business environments and rules and intelligently correlate data insights with business goals.
  • Insight into the closed loop of action: Transform abstract problems into executable tasks, automate their execution, and close the loop from discovery to solution.
  • Self-Learning Evolution: Enhance capabilities based on user interaction, continuously optimize, and build a self-evolving enterprise data system.
• Data convergence and value unlocking::
  • data fusion: Integrate structured and unstructured data to build a unified view of data and break down data silos.
  • Business Context Understanding: Accurately match business needs, provide targeted support, and ensure that analysis results are relevant.
  • requirements disassembly: Breaking down complex requirements into specific tasks and addressing them one by one to ensure efficient execution.

How to use Data Agent

• Register & Login: Access to the Volcano Engine Data AgentOfficial websiteIf you are a registered user, follow the instructions on the page to complete the registration process and log in to the system. When registering, you need to fill in relevant information to ensure account security.
• data access::
  • Preparing the data source: Organize the data to be analyzed.
  • Access to data sources: On the Data Agent platform, follow the guidelines for accessing data sources.
  • Configuring data permissions: Set data access rights according to actual needs to ensure data security and compliance.
• Configuration and Customization::
  • Business Scenario Configuration: Select or configure applicable business scenario templates, such as marketing analytics, customer operations, etc., based on the specific business needs of the organization.
  • Customized miniatures: If more accurate analysis is needed, customize the miniatures and adapt the algorithms to specific business needs.
  • Setting Analysis Goals: Define the goals of data analysis, e.g., sales growth, increased customer satisfaction, etc.
• Interaction and Analysis::
  • conversational interaction: Interact with Data Agent in natural language, ask questions directly, and the system gives answers quickly.
  • Real-time monitoring and early warning: Set real-time monitoring indicators and warning rules, when the data reaches the set threshold, the system automatically pushes the warning information to help find the abnormality in time.
  • Generating reports: Data Agent automatically generates detailed analysis reports based on issues.

Official Example of Data Agent

• Prompt: What are some of the hotter stocks of late?

• Prompt: Analyze the effectiveness and ROI of the channel promotion of the game Dark Star Breakout and drill down data to analyze the reasons.

• Prompt: Generate an analysis of the company's operations for the last 30 days.

Core Benefits of Data Agent

• deep contextual understanding: Accurately correlate data with business objectives to ensure that analytics are relevant to actual needs.
• Multimodal data analysis: Supports a wide range of data types, including text, image, and voice, to provide a comprehensive view.
• Automation and real-time: Automate report generation, monitor metrics in real time, and respond quickly to market changes.
• Intelligent Interaction and Personalization: Conversational interactions that provide personalized analysis and recommendations.
• Self-learning and evolution: Continuous optimization capabilities to adapt to changing business needs.
• Data Fusion and Unified View: Integrate various data sources to break down data silos and improve management efficiency.
• Efficient decision support: Closing the loop from data insights to action execution, enabling accurate decision-making.

Who can use Data Agent?

• Business decision support: Real-time data analytics to facilitate accurate decision-making and monitoring indicators to warn of risks.
• Intelligent Marketing Optimization: Customer data analytics enable personalized marketing to improve campaign effectiveness and return on investment.
• Customer Management Enhancement: Analyze customer behavior to provide personalized service, enhance the experience, and increase loyalty.
• Knowledge sink sharing: Structuring tacit knowledge, depositing it into a knowledge base, and facilitating team sharing.
• Efficiency gains: Automate reporting and data analysis tasks to reduce manual effort and focus on high-value work.