Velvet

What is Velvet?

Velvet is a unified data platform built specifically for product and engineering teams at fast-growing startups. It’s designed to make working with data much simpler and more powerful. With Velvet, you can run complicated SQL queries, use AI to quickly sort through huge amounts of data, and easily share your findings. You can turn your queries into interactive visuals like tables and graphs, or even set up alerts that the whole team can see and use. Velvet also lets you access real-time data through query API endpoints and store as much data as you need from all sorts of places – databases, other tools, or event streams. Essentially, it helps you build real-time features, collect data as it happens, and keep track of how your data changes over time. By making data transformation easier, fostering team collaboration, and providing AI help for analysis, Velvet really helps streamline how you handle data and develop your products.

Who created Velvet?

Velvet was developed by a team connected to the platform itself. It officially launched on December 6, 2023. The main idea behind Velvet was to give product and engineering teams at high-growth startups the tools they need. This means letting them run complex SQL queries, use AI to make sense of large data sets, work together smoothly, and share data visualizations with everyone on the team. Key features include using real-time data, setting up query API endpoints to store unlimited amounts of data, and empowering team members to act like data engineers.

What is Velvet used for?

Velvet is incredibly versatile and can be used for a variety of tasks:

• Product Development: This includes writing and running complex SQL queries, using AI to parse massive data sets, capturing data in real-time, turning queries into useful tables, graphs, or alerts, and building product features that are driven by real-time data.
• Optimizing Data Workflows: It helps make your entire data process run more smoothly.
• Shipping Real-Time Features: Get your data-driven features out the door faster.
• Supporting Data Collaboration: Makes it easier for teams to work together on data.
• Analyzing AI Features: You can evaluate the costs, how much you’re using, and how well your AI models, features, and different versions are performing.
• Data Visualization: Turn your queries into clear visual formats like tables and graphs.
• Data Transformation: Query data from different sources, deliver real-time features, and adjust your data workflows.
• Cross-Source Data Queries: Easily query data that comes from multiple different places.
• Data Analysis from Third-Party Tools and Events: Analyze information coming from external tools and user events.
• Parsing Large Data Volumes with AI: Use artificial intelligence to efficiently process huge amounts of data.
• Performing Complex SQL Queries: Handle sophisticated SQL queries with ease.
• Capturing Real-Time Data: Collect data as it happens from various sources.
• Transforming Queries into Visuals: Convert your queries into easily understandable tables, graphs, or alerts.
• Shipping Real-Time, Data-Driven Product Features: Get dynamic, data-powered features into your products quickly.
• Accelerating Development Workflows: Speed up how your team builds and ships.
• Analyzing Data from Third-Party Tools and Events: Gain insights from external sources and user interactions.
• Using AI to Parse Vast Amounts of Data: Leverage AI for efficient processing of extensive datasets.
• Facilitating Data Transformation: Make the process of changing and preparing data simpler.
• Supporting Collaboration of Data Engineering: Help data engineers work together more effectively.

Who is Velvet for?

Velvet is a great tool for:

• Software engineers
• Data engineers
• Product Managers

How to use Velvet?

Ready to get started with Velvet for your data needs? Here’s a simple guide:

1. Tackle Complex SQL Queries: Start by writing and running your most complex SQL queries right within Velvet.
2. Leverage AI for Data Parsing: Use the built-in AI to efficiently parse through large volumes of data, saving you time and effort.
3. Capture Real-Time Data: Make sure you’re capturing real-time data from all your sources to get the most up-to-date insights.
4. Transform Queries into Visuals: Turn your queries into clear tables, insightful graphs, or actionable alerts for easy visualization.
5. Boost Collaboration and Workflow: Share your visualized data insights across your team to foster better collaboration and streamline your workflow.
6. Create Query API Endpoints: Save your frequently used queries as API endpoints. This makes accessing relevant data quick and straightforward.
7. Analyze Data from Multiple Sources: Dive into data from third-party tools and events to get a complete picture.
8. Embrace a Unified Data Platform: Make the most of a single platform that simplifies data access and optimizes your entire workflow.

By following these steps, you’ll be well on your way to unlocking Velvet’s full potential and really improving your data analysis and product development processes.