Powerful AI assist for data, now in Public Beta
Highlighted questions and answers from a live joint Snowflake and Hex session
Learn how to describe, summarize, and find patterns in the data from a single variable.
Learn how the computational engine for notebooks functions.
Learn how to access the most popular data sources with Python in Jupyter Notebooks
A detailed guide to data exploration in Jupyter with Python and Pandas.
Behind-the-scenes look at how Hex built features that integrated with Snowflake.
How to use Hex, LangChain, and OpenAI to use natural language to query your database
Learn how to share Jupyter notebooks with technical and non-technical audiences.
Learn how to create charts using Matplotlib, Plotly, and Seaborn
How one data team transformed tedious, manual reporting tasks into seamless, automated workflows
Announcing our partnership with Google and how we’re enabling larger data workflows for thousands of users
Using modern data tools to discover modern opportunities for exploration
Product analytics on top of warehouse allows for deeper insights into activation, retention, and churn.
End to end tools make the modern analytics workflow faster
What coal and Jevons’ paradox tell us about AI and data
Or: this blog post has made $0
Practical examples of common dimensionality reduction algorithms in Python
Building an intuition around a common data science technique
SQL is for more than just reading and writing to your database. Understanding the core components of this language lets you be much more efficient with your data analysis.
The best tools to bring structure and meaning to data, and enable insightful analysis.
Analyze, model, and explore datasets without having to move data outside of a secure and governed Snowflake account.
Learn about the simpler text processing cousins of LLMs like GPT-4
Query Iceberg tables and build interactive reports on top with Hex
Elevate your decision-making process by turning raw data into actionable insights and strategic outcomes
Leverage Python’s versatility and SQL Server’s robustness with the pyodbc library to easily connect and interact with your database
Announcing our Elite Partner Status and how we’re speeding up data workflows for thousands of users
Using computers to programmatically understand and interpret human language
Curate your workspace with a flexible and powerful organizational framework
Reactive notebooks allow for better interpretability, reproducibility, and performance
Announcing our partnership with Sequoia
Get data into pandas without downloading csvs
Why dbt Labs’ acquisition of Transform is great for data stacks
AI tools meant to augment – not replace – human insight. Now in private beta.
Infinitely scalable data visualization, with a more permissive license
Stop repeating yourself repeating yourself reaepting yuroslef rpaetnig ouylefs
Point-and-click visual filtering, an all-new chart cell, custom color palettes, and more
Learn how to prepare text data for NLP tasks
Learn how to classify the sentiment in a body of text
How Human Interest’s data team empowers stakeholders across the company to use analytics every day
What comes before sophisticated data analysis and modeling?
Announcing our partnership, product integrations, and how we’re changing data workflows for thousands of users
Compare versions of a product/service in order to observe which one performs the best.
Tracking user events, actions, and drop-off
Here’s what we learned and how you can avoid it
Querying one of the most commonly used databases from Python
A comprehensive guide on how to create dbt packages with working code examples, and an open-source repo that you can build from.
Analyze groups of customers to understand retention, predict churn, and find other patterns
A supercharged, collaborative, cloud-native way to notebook
Four steps to read data from your BigQuery warehouse directly into Python
Implementation of a binary classification algorithm in Python
We spoke about Bluecore’s revenue forecasting app, how the team prioritizes projects and measures success, reasons for adopting Hex, and more
A common algorithm used to find the best-fitting line between two or more variables
A new Metrics cell, dbt-flavored SQL in Hex, and more!
We spoke about Bluecore's data team and modern data stack, use cases for Hex, and more
Extracting from a production PostgreSQL database and loading into Snowflake
A simple and elegant way to deploy machine learning models
A New Way to Think About Data Roles
Turning your Python data visualizations into beautiful interactive dashboards
Enabling Exploratory Analysis with SQL & Python
Why data teams use notebooks, and how to get them up and running for coding and exploratory analysis
Trigger Hex apps right from Airflow and Dagster— or plug into the API and build something completely custom
How to build a lead scoring model that actually serves stakeholders
Leaving fragmentation, local files, and version control hell in the past
Two and a half ways to query Pandas DataFrames with SQL
Four steps to read data from your warehouse directly into Python
Bringing all the power of dbt’s documentation site, straight into Hex
Bringing together SQL, Python, and no-code in Hex’s magical notebooks
Why it's time to "break up" with your favorite SQL feature
Our tools for exploration and analysis are living in the past.
Learn how to read data from your Redshift warehouse directly into Python
Query mode, Chained SQL, and Python pushdown for everyone
Plus, Snowflake Partner Connect and Premier Partner status
Streamlining analytics engineering workflows with Hex
Announcing a new, richer way to embed data from Hex into Notion docs
Introducing an all-new way to version work in Hex
Turning simple queries into impactful artifacts
SQL finally gets literate programming
Designing and engineering a new app layout engine from scratch
Data teams are still struggling to have impact.
Data teams are still struggling to have impact. We raised some money to help.
Why we're excited to partner with Databricks to power the next generation of analytics workflows
Part 2: Barriers to STEM equality and boundary setting
How to run a hackathon for data in the age of the modern data stack
Part 1: How a PhD astrophysicist thinks about data
Embedding cells and apps for fun and profit
High-impact data work isn’t just about churning out analysis; it’s about creating knowledge.
Why you should pair your powerful data warehouse with a collaborative data workspace
A more beautiful and useful way to visualize dataframes.
Some more money stuff, and our partnership with dbt Labs
Our new dbt integration and partnership with dbt Labs
Announcing a new, ✨ magic ✨ way to work with notebooks and build data apps
Security is our most important job. This report reflects how seriously we take our obligations for customer data.
Python or SQL? Why not both?
SQL IDE, Chart Cell, Scheduling, and more!
An interview with Mona Khalil, Data Scientist at Greenhouse
What we're doing, why we're doing it, and some money stuff
An interview with the author of Practical Business Python
Communicating data work is as messy as ever.
or: How I Learned to Stop Worrying and Love the Atomic Operation
The only path around the 2.0 tar pit is incrementalism - replacing a legacy platform through small, deliberate steps.
Next time you get asked to justify the ROI for your team, don't. Sit back, and let others tell the story for you.
Truly empowering users doesn’t mean getting rid of code, but embracing it.
