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Introducing Explore — an all-new experience for slicing, dicing, and visualizing data. Explore gives everyone the analytical powers of Hex in a familiar, no-code UI, with: 🐉 Drag & drop - Add dimensions and measures to a visual canvas 🎨 Pivots & viz - Customize, color, and group data...

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Hex

7,002 subscribers

25,325 Aufrufe • vor 1 Jahr •via X (Twitter)

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5 Kommentare

Profilbild von Abhi Sivasailam
Abhi Sivasailamvor 1 Jahr

Big.

Profilbild von Dominik Moritz
Dominik Moritzvor 1 Jahr

Again, killing it.

Profilbild von Scott Condron
Scott Condronvor 1 Jahr

The value of being able to consume dashboards and then leap off to explore resonates with me so much. Mostly because I feel just a little bad every time I ask the data team for ‘one more slice’ that may or may not reveal any actual insights.

Profilbild von pun life
pun lifevor 1 Jahr

amazing set of features

Profilbild von Luca Baggi
Luca Baggivor 1 Jahr

You should’ve called it Hexplore 👻 congratulations for the launch!

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Today we're taking the powerful data tools we've built for technical practitioners, and opening them up to everyone! We're releasing end-to-end no-code workflows with: ∑ Spreadsheet-style calculations 🧮 Data browsing 🔏 Updated governance features 🤖 AI speed and accuracy improvements These new workflows live right alongside our existing SQL, Python, and AI tools, so everyone— regardless of technical experience— can come together in Hex to ask and answer questions with data. Watch the launch video below, or read on into the thread for all the details!

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Microsoft has launched a powerful new data analysis tool! Introducing Data Formulator, a 100% open-source LLM-powered, no-code tool that transforms data in a snap and creates stunning visualizations. Key features include: 🤖 AI-powered data transformation 🖱️ Interactive drag-and-drop UI for visualizations 💬 Seamless blend of UI & natural language inputs But that’s not all: You can even create charts beyond your initial dataset. Data Formulator automatically identifies extra computation needs, generates fields for you, and outputs the final visualization. Find the GitHub repo in the next tweet! _____ Find me → Akshay 🚀 ✔️ For more insights and tutorials on AI and Machine Learning.

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kwindla

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In a world where historical data is no longer enough, we’re introducing the ✨ NEW ✨ Crunchbase: AI-powered predictive intelligence. We predict private market movements, from funding to acquisitions, and identify the companies set up for success. 🔮 Explore more at
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Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

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Strategy is proud to announce a strategic partnership with marking an important milestone in their AI journey. Strategy makes AI reliable on enterprise data, and is committed to helping organizations transform data into actionable insights and make faster, more informed decisions. Through this collaboration, we are enabling to further leverage data as a strategic asset across their organization, powered by Strategy Mosaic, our Universal Semantic Layer that gives AI the business context it needs to produce consistent, governed results. This partnership aligns with long-term vision of embedding AI and data-driven decision-making into every aspect of their business. By enhancing their analytical capabilities with Strategy, we are helping to build a stronger foundation for innovation, operational excellence, and customer value. As continues its AI-first journey, Strategy is proud to play a role in supporting their growth and shaping the future of their organization. #AI #SemanticLayer #InsuranceTech #StrategyMosaic
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Strategy is proud to announce a strategic partnership with marking an important milestone in their AI journey. Strategy makes AI reliable on enterprise data, and is committed to helping organizations transform data into actionable insights and make faster, more informed decisions. Through this collaboration, we are enabling to further leverage data as a strategic asset across their organization, powered by Strategy Mosaic, our Universal Semantic Layer that gives AI the business context it needs to produce consistent, governed results. This partnership aligns with long-term vision of embedding AI and data-driven decision-making into every aspect of their business. By enhancing their analytical capabilities with Strategy, we are helping to build a stronger foundation for innovation, operational excellence, and customer value. As continues its AI-first journey, Strategy is proud to play a role in supporting their growth and shaping the future of their organization. #AI #SemanticLayer #InsuranceTech #StrategyMosaic

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I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

Matt Dancho (Business Science)

11,799 Aufrufe • vor 1 Jahr

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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 Aufrufe • vor 1 Jahr

GeoLibre v2.1 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release adds a QGIS-style Browser panel for exploring data from one place, animated route playback with video export, Wikipedia knowledge cards, and Mapillary street-level images. What's new in v2.1.0 - Browser panel (Data Source Manager): explore and add data from one place. Browse map services, connect to PostGIS databases and drill into their schemas and tables, open local files, and save Favorites, all with full keyboard navigation. - Route animation: send a marker along any line layer, follow the track in 3D with camera controls, and export the whole animation as an MP4 video. - In-browser object detection: run ONNX/YOLO models directly in the webview, with no server or Python required. - Map recording: capture the map canvas, or a drawn bounding box, straight to a video file from the browser. - Native-resolution photo viewer: view geotagged photos at full detail right on the map. - Wikipedia knowledge cards: click any place to pull up its Wikipedia summary and info card. - More planetary basemaps: USGS imagery for nine more celestial bodies, plus a new OpenAerialMap imagery search plugin. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre
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GeoLibre v2.1 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release adds a QGIS-style Browser panel for exploring data from one place, animated route playback with video export, Wikipedia knowledge cards, and Mapillary street-level images. What's new in v2.1.0 - Browser panel (Data Source Manager): explore and add data from one place. Browse map services, connect to PostGIS databases and drill into their schemas and tables, open local files, and save Favorites, all with full keyboard navigation. - Route animation: send a marker along any line layer, follow the track in 3D with camera controls, and export the whole animation as an MP4 video. - In-browser object detection: run ONNX/YOLO models directly in the webview, with no server or Python required. - Map recording: capture the map canvas, or a drawn bounding box, straight to a video file from the browser. - Native-resolution photo viewer: view geotagged photos at full detail right on the map. - Wikipedia knowledge cards: click any place to pull up its Wikipedia summary and info card. - More planetary basemaps: USGS imagery for nine more celestial bodies, plus a new OpenAerialMap imagery search plugin. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

Qiusheng Wu

12,139 Aufrufe • vor 2 Monaten

Introducing PostHog 3000 & Notebooks 🎉 As an end of year gift to our awesome users, we've released a major overhaul of the PostHog user experience. Our goal with this redesign is to make PostHog feel less like a SaaS app and more like a dev tool. ✅ It's got dark mode! ✅ It's got data density! ✅ It's got side panels! ✅ It's got... notebooks? Notebooks is a new, free feature that's integral to the PostHog 3000 experience. Think of them as an ever-present place to collect data, explore it, add context, and share with others. Investigating a bug report? 🐞 Drag and drop session replays into a notebook. Researching a new idea? 💡 Collect insights and add them to your proposal seamlessly, alongside survey results or cohorts. Planning a launch? 🚀 Embed the feature flags, events, persons, or cohorts you'll need to deploy changes and track success. Notebooks make analyzing data and sharing your findings effortless – see the video demo for more. We have way more planned for Notebooks and PostHog 3000 in 2024, such as: 🔔 A new activity feed 📔 Notebook templates ⌨️ Way more keyboard shortcuts 💬 Comments, replies and mentions (coming very soon) We hope you enjoy the update and, as ever, please share your feedback (it's even easier to do in PostHog 3000!). Thank you for your support. 🙌
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Introducing PostHog 3000 & Notebooks 🎉 As an end of year gift to our awesome users, we've released a major overhaul of the PostHog user experience. Our goal with this redesign is to make PostHog feel less like a SaaS app and more like a dev tool. ✅ It's got dark mode! ✅ It's got data density! ✅ It's got side panels! ✅ It's got... notebooks? Notebooks is a new, free feature that's integral to the PostHog 3000 experience. Think of them as an ever-present place to collect data, explore it, add context, and share with others. Investigating a bug report? 🐞 Drag and drop session replays into a notebook. Researching a new idea? 💡 Collect insights and add them to your proposal seamlessly, alongside survey results or cohorts. Planning a launch? 🚀 Embed the feature flags, events, persons, or cohorts you'll need to deploy changes and track success. Notebooks make analyzing data and sharing your findings effortless – see the video demo for more. We have way more planned for Notebooks and PostHog 3000 in 2024, such as: 🔔 A new activity feed 📔 Notebook templates ⌨️ Way more keyboard shortcuts 💬 Comments, replies and mentions (coming very soon) We hope you enjoy the update and, as ever, please share your feedback (it's even easier to do in PostHog 3000!). Thank you for your support. 🙌

PostHog

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