Query your warehouse, uploaded files, or dataframes directly with SQL.
Izzy Miller
Enhance your marketing and sales strategies with a detailed Customer Segmentation model built using SQL & Python. Using K-Means clustering, you can intelligently segment your customer base into distinct groups based on purchase behavior, demographics, and other significant characteristics, enabling targeted marketing campaigns and personalized customer experiences. Hex lets you use Python's machine learning libraries for feature scaling and encoding, and K-Means for defining clear, actionable customer clusters— and also makes it easy to power these analyses with data right from your SQL warehouse.
Detect and analyze anomalies in your dataset using robust Outlier Detection methods. With Hex, you can easily integrate Python's Scikit-learn, use IQR techniques, or apply Z-Scores to pinpoint outliers. Streamline your data analysis, ensure quality, and drive accurate results by efficiently identifying and addressing these deviations.
See how to use data science to enhance inventory decisions with this comprehensive project focused on analyzing, predicting, and optimizing inventory levels. Using historical sales data and trends, we build a robust predictive model with Python and SQL that factors in seasonality, trends, and demand fluctuations. Hex's seamless integration of SQL, Python, and intuitive visualization tools makes it easy to explore inventory data, build predictive stock-level models, and communicate findings in an easy-to-understand, interactive report. This model ensures you maintain the optimum level of stock during peak periods, thus minimizing costs and preventing out-of-stock scenarios.
Hex provides a flexible workspace to parse text data like social media posts and perform sentiment analysis with SQL and Python. Hex's polyglot environment means you can use Python packages like NLTK and SpaCy directly on data from your warehouse— or in this case, just a good old fashioned logistic regression against a simple .csv file. From simple 5-minute project to production deployed data applications, Hex makes it easy to perform any kind of sentiment analysis on social media (or any) data.
Hex is the most powerful development environment for prototyping and deploying predictive models. With direct SQL access to your data warehouse, a polyglot environment for developing and deploying models, and a built in app builder, the data science feedback loop has never been tighter.
Period over period analysis in a notebook has never been easier or more flexible. With a powerful Python workspace that also supports SQL, you can build a fully interactive report for anyone, and give them the tools to customize their timeframes and periods of interest. When you're done, just click "Publish" and your results are instantly shareable.
Reduce customer churn with predictive insights. Discover how our Random Forest model can forecast potential customer drop-offs before they happen, saving you the higher costs of acquiring new clients. Dive into our project to see how we turn data into retention strategies for your business.
Like Google Docs, but fully interactive and synced to your data in real time. Build long-form analysis using SQL, Python, or No-Code, and publish beautiful reports that end users will love.
Understand and optimize your customer's lifetime value (CLV) with this comprehensive example of using Python and SQL to model future spending habits. You'll learn the basics of LTV modeling, explore several different scenarios like buy-till-you-die and gamma-gamma, and get a template of an interactive report on top of these models that anyone at your organization can use. Hex makes it easy to explore datasets, build complex predictive behavioral models, and then communicate findings in an interactive report— all from the same tool.
All the organizational power of code notebooks, tailor-made for your SQL workflows. Chain SQL queries, join across data sources, and access cloud-scale data in a collaborative SQL IDE.
Don't limit yourself to traditional, old-fashioned BI. Hex lets you turn even the most flexible and complex analyses into beautiful, easy to use dashboards.
Discover how Hex data scientists and analysts use Hex for everything from dashboards to deep dives.
Table display cells are a way to visualize, filter, and format tabular data without writing any code. Simply choose a dataframe and use the Table display settings to apply any fitlers, change the data format of any column, hide any column, wrap text.
Hex’s first-class Python support unlocks a world of opportunity for data exploration.
Map cells let you visualize geographic data in a customizable interactive map.
Chart cells let you visualize and explore the dataframes in a Hex project, without writing code.
Input parameters are a core, unique part of Hex. Input parameters can be created in the Notebook view and then added, optionally, to an app.
Text and Markdown cells let you add narrative, explanations, and context to your data project.
