Building AI Apps with
Standard Metrics Data: Vector Search
for Smarter Insights
Making Standard Metrics data AI-ready and accessible for smarter apps by seamlessly connecting Standard Metrics, Zilliz Cloud, and fivetran.
What is Standard Metrics and What's Its Data Like?
Standard Metrics is a business analytics tool that aggregates financial and operational data to provide actionable insights. It handles structured data including sales performance, financial statements, and operational efficiency metrics, providing businesses with dashboards and reports to monitor their health and progress. Standard Metrics helps organizations streamline their reporting processes and make informed decisions based on comprehensive, real-time data analysis.
Challenges for Building AI Apps with Standard Metrics Data
Unstructured Data
Much of Standard Metrics’s data is unstructured and multimodal. Standard database queries struggle with such text-heavy information, making it difficult to unlock its full potential.
Data Silos
Standard Metrics data often exists in isolation, making it challenging to integrate with other enterprise systems or data sources.
Scalability
Massive amounts of user interactions are logged daily, and processing and querying this data in real time requires robust infrastructure, especially when building AI-driven applications.
Personalization
AI apps require deep insights into customer behavior to offer personalized experiences. However, standard searches and SQL queries don’t adequately surface the relationships and similarities hidden in Standard Metrics data.
Fueling Standard Metrics AI Apps with Vector Search for Smarter Insights
Making Unstructured Data Searchable
Vector search enables AI to explore unstructured Standard Metrics data like text and images by comparing the meaning and context of each data point. This allows your AI apps to uncover actionable insights that were previously buried in complex records.
Going Beyond Keywords with Semantic Search
With vector similarity search, your AI apps are no longer limited to basic keyword matching. Vector search solutions like Zilliz Cloud perform deep, context-aware searches, identifying patterns and similarities across Standard Metrics data that traditional methods can’t reach.
Uncovering Hidden Relationships
Vector search finds subtle trends and connections within unstructured data. By identifying these hidden patterns, your AI apps generate more accurate predictions, smarter recommendations, and better overall results.
Scalability for Real-Time AI
Designed for speed and scale, vector search engines like Zilliz Cloud can process massive Standard Metrics datasets in real-time. Whether it’s handling billions of records or delivering instantaneous insights, vector search ensures your AI applications can perform at peak efficiency.
Connect Standard Metrics, Zilliz Cloud, and fivetran to Unlock Instant, AI-Ready Insights
The seamless integration of fivetran and Zilliz Cloud takes the complexity out of building AI-powered apps using unstructured data from Standard Metrics and any other sources. With just a few clicks, you can deploy fast, efficient, and scalable search solutions, empowering your AI applications to deliver smarter insights.
1.
Unstructured data from Standard Metrics flows to fivetran.
2.
fivetran pre-processes and transforms the data into vector embeddings using OpenAI embedding services.
3.
The Zilliz Cloud connector channels the processed vector data into the Zilliz Cloud vector database in real time, ensuring instant availability for AI-powered tasks.
4.
Zilliz Cloud performs vector similarity searches to find relevant information to user queries.
5.
LLMs leverage the provided contextual information to generate meaningful, context-driven insights.
How to Build AI-powered Search for Every Data Source with Fivetran and Zilliz Cloud
4 min watch
Try This Integration for Free
Make your data AI-ready by connecting Standard Metrics, fivetran, and Zilliz Cloud.
Frequently Asked Questions
New to Zilliz Cloud integrations? You're not alone. Here are some answers to common questions about how Zilliz Cloud works with Standard Metrics and fivetran.
What is a vector database?
Why integrating Standard Metrics, fivetran, and Zilliz Cloud for your GenAI apps?
What types of Standard Metrics data can I store and search in Zilliz Cloud?
What is Zilliz Cloud?
What is Fivetran?