Collaborative data science & analytics on the Data Cloud.
Hex was built to be cloud-native, and to work with Snowflake’s Data Cloud. Its unique architecture and tight integrations let users move beyond limits of traditional notebooks, and modernize their workflows for the cloud. Most - or all! - data processing can be pushed down to the Snowflake Data Cloud, taking advantage of Snowflake’s scalable compute and advanced caching. Discovering insights and building apps on data stored in Snowflake using Hex’s data and analytics workspace takes just minutes.
Hex also provides first-class support for Snowflake’s developer framework, Snowpark. The integration with Hex’s notebook UI provides an elegant front end for data scientists and analysts to connect to data in the Snowflake Data Cloud, do exploration and analysis in SQL and Python, build interactive data apps, and share them broadly.
Hex is built for data teams. Every day, data scientists, analysts, analytics engineers, and ML practitioners use Hex to connect to the Snowflake Data Cloud, write SQL and Python in a collaborative notebook interface, and build interactive data apps that can be shared with anyone. With Hex’s unique architecture, reactive compute model, and first-class SQL support, notebooks exist as first-class citizens in this new era.
With the Hex / Snowpark integration, SQL users who are proficient in Snowflake have a low-barrier entry point to try doing data science work in Python, and Python users can take full advantage of the power and scalability of the Snowflake Data Cloud for data science workflows.
Data consumers such as internal stakeholders or customers also rely on Hex, which makes it easy to access apps built by data teams, ask questions, and make better decisions. The feedback loop provided by Hex allows consumers to collaborate in an ongoing fashion with data teams to ensure they’re getting accurate, trusted information.
Hex also empowers data leaders. They use Hex — in particular, the Knowledge Library — to gain visibility into what apps their teams have created, and how they’re being used across the business.
Exploratory and ad hoc analyses: Answer a question like “Why did costs spike this month?” by investigating anomalies in production data, or figure out if a new feature launch was successful by looking at user adoption.
Production data apps: These are essentially flexible, interactive, live dashboards. They can be embedded into tools like Notion or Confluence, and customer-facing, for sharing insights back to clients, partners, or other third parties. Hex apps can help to stay ahead of customer churn in one business unit, forecast a manufacturer's order volumes and shipping logistics, or share usage data to inform the product roadmap. Scheduled runs can be embedded in the app to ensure the data is always fresh.
Interactive data stories: Combine rich text and interactive, live visualizations to tell a better story than what would be possible with slides or reports alone. For instance, a researcher can use Hex to break down a complex dataset to find potentially habitable planets, or to build a better pricing model for a hot commodity.
Hex customers work faster and more collaboratively, deliver quick time to value from data products, and accelerate the pace of innovation.