The Analytics Platforms solutions below are the most common alternatives that users and reviewers compare with Hex. Analytics Platforms is a widely used technology, and many people are seeking high quality, simple software solutions with data discovery, predictive analytics, and search. Other important factors to consider when researching alternatives to Hex include visualization tools and features. The best overall Hex alternative is Tableau. Other similar apps like Hex are Mode, Deepnote, Microsoft Power BI, and Looker. Hex alternatives can be found in Analytics Platforms but may also be in Python Integrated Development Environments (IDE) or Big Data Processing And Distribution Systems.
Tableau Server is a business intelligence application that provides browser-based analytics anyone can learn and use.
Mode is an analytics platform that helps data driven teams analyze, visualize, and share data.
Deepnote is a new kind of data science notebook. Real-time collaboration, zero setup, and completely cloud-based.
Looker supports a discovery-driven culture throughout the organization; its web-based data discovery platform provides the power and finesse required by data analysts while empowering business users throughout the organization to find their own answers.
Making big data simple
ThoughtSpot is the AI-native Intelligence Platform company for the enterprise. With natural language and AI, ThoughtSpot empowers everyone in an organization to ask data questions, get answers, and take action. Code-first for data teams and code-free for business users, ThoughtSpot is intuitive enough for anyone to use, yet built to handle large, complex cloud data at scale. Customers like NVIDIA, Hilton Worldwide, and Capital One are unlocking the full potential of their data with ThoughtSpot.
Give business teams the freedom to analyze cloud data in real time without limits. Sigma provides the full power of SQL without coding, cloud flexibility, and an intuitive spreadsheet interface.
Jupyter Notebook is an open-source, web-based interactive computing environment that enables users to create and share documents containing live code, equations, visualizations, and narrative text. It supports over 40 programming languages, including Python, R, Julia, and Scala, making it a versatile tool for data science, scientific computing, and machine learning. Key Features: - Interactive Computing: Allows real-time code execution and immediate feedback, facilitating an interactive development process. - Multi-Language Support: Supports numerous programming languages, enabling flexibility in project development. - Rich Text Integration: Incorporates Markdown for formatting text, creating headings, lists, and embedding links alongside code. - Data Visualization: Integrates seamlessly with libraries like Matplotlib and Seaborn to produce dynamic, inline visualizations. - Notebook Sharing: Enables easy sharing of notebooks via email, GitHub, or conversion to formats like HTML and PDF. - Extensible Architecture: Supports extensions and plugins, allowing for customization and additional functionality. - Kernel Flexibility: Allows switching between different programming languages within the same notebook. Primary Value and User Solutions: Jupyter Notebook streamlines the process of developing, documenting, and sharing computational workflows. Its interactive environment promotes reproducibility and transparency in research, making it an invaluable tool for data scientists, educators, and researchers. By combining code execution, rich text, and visualizations in a single document, it enhances collaboration and simplifies the communication of complex ideas.
Sisense is an end-to-end business analytics software that enables users to easily prepare and analyze complex data, covering the full scope of analysis from data integration to visualization.