# Data visualization Data visualization is the practice of representing data graphically through charts, maps, dashboards, and other visual forms to communicate information, reveal patterns, and support analysis. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Open Sauce and GPS time were my summer AI Antiseptics DevFeed: [Open Sauce and GPS time were my summer AI Antiseptics]() Original publisher: [Read original article]() Author: jeff@jeffgeerling.com (Jeff Geerling) Published: 2026-07-22T14:00:00Z Content type: opinion Language: en Sources: [Jeff Geerling]() Topics: [Artificial Intelligence](), [Data visualization](), [MicroPython](), [Claude](), [datasets](), [Code]() Tags: [ai](), [badge](), [claude](), [coding](), [data-visualization](), [electronics](), [experimentation](), [gps](), [micropython](), [open-sauce](), [projects](), [time](), [videos](), [visualization]() ### AI overview The author describes using Claude to build a 2,141-line MicroPython Badgeware app for a Pimoroni Tufty 2350 and Adafruit PA1010D GPS module. The GPS Time Badge uses GPS data to discipline the badge's internal real-time clock, although timing accuracy was limited by the hardware and BadgeOS architecture. The author also logged GPS satellite and fix-quality data and used Claude to create an interactive visualization, highlighting data visualization as a practical use of AI tools. ### Source excerpt In the midst of our AI slop revolution, traveling to the West coast for Open Sauce this past weekend was the perfect antiseptic for rising costs, summer heat, and online divisiveness. It's ironic, then, that I used Claude to vibe code my Tufty GPS Time Badge. Partly due to time constraints, and partly because I wanted to see if I could complete a personal project end-to-end, without editing a line of code, I throw my requirements at Claude and ultimately came up with this 2141-line MicroPython app for Pimoroni's Badgeware ecosystem. ## 3 Questions: Beyond data-driven aesthetics DevFeed: [3 Questions: Beyond data-driven aesthetics]() Original publisher: [Read original article]() Author: School of Architecture and Planning Published: 2026-06-29T18:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Data visualization](), [Algorithms](), [Mathematics](), [Computer science](), [Machine learning]() Tags: [3-questions](), [aesthetic-judgment](), [ai](), [ai-and-aesthetics](), [alexandros-haridis](), [algorithms](), [alumni-ae](), [applied-arts](), [architecture](), [artificial-intelligence](), [beyond-data-driven-aesthetics](), [computational-aesthetics](), [computer-science-and-technology](), [data](), [data-visualization](), [design](), [design-computation](), [exhibits](), [interactive-installations](), [interview](), [machine-learning](), [mit-architecture](), [mit-exhibits](), [mit-keller-gallery](), [mit-sa-plus-p](), [philosophy](), [research](), [school-of-architecture-and-planning](), [shape-grammars](), [special-events-and-guest-speakers]() ### AI overview An MIT Keller Gallery exhibition by Alexandros Haridis examines the history of aesthetic judgment and creative production in computing, connecting architecture, design computation, algorithms, and machine-learning systems. ### Source excerpt In a new Keller Gallery exhibition, Alexandros Haridis SM '17, PhD '22 traces centuries of ideas about aesthetic judgment and explores how design can make complex computational systems visible. ## How I Validated Design Decisions Before Writing Production Code DevFeed: [How I Validated Design Decisions Before Writing Production Code]() Original publisher: [Read original article]() Author: andyacevedo Published: 2026-06-04T01:29:47Z Content type: article Language: en Sources: [Slack Design]() Topics: [AI-assisted coding](), [Data visualization](), [Algorithms](), [Figma]() Tags: [ai-assisted-coding](), [algorithms](), [data-visualization](), [figma](), [projects](), [uncategorized]() ### AI overview A Slack designer explains how AI-assisted coding can make design exploration practical before production work begins. Interactive prototypes tested gallery layout algorithms and max-width strategies against real screen-size data, revealing edge cases and helping evaluate which decisions hold up across conditions. ### Source excerpt The biggest shift AI has brought to design isn't that designers can now write production code. It's that we can finally generate evidence before committing to anything. There's a lot of conversation about AI affecting production: designers pushing code and shipping something closer to the final product. That matters. But the bigger opportunity is even [...] The post How I Validated Design Decisions Before Writing Production Code appeared first on Slack Design. ## Mini Shai-Hulud npm Attack: AntV Ecosystem Compromise (May 2026) DevFeed: [Mini Shai-Hulud npm Attack: AntV Ecosystem Compromise (May 2026)]() Original publisher: [Read original article]() Published: 2026-05-19T00:00:00Z Content type: news Language: en Sources: [Chainguard: Unchained]() Topics: [npm packages](), [supply-chain-security](), [Malware](), [Data visualization](), [Aeternum](), [stripe](), [Raycast extension](), [React UI animations]() Tags: [2026](), [antv](), [chainguard-libraries](), [chainguard-npm](), [malware](), [mini-shai-hulud](), [npm](), [npm-malware](), [npm-packages](), [react](), [supply-chain](), [supply-chain-security]() ### AI overview The article reports that a compromised npm maintainer account pushed malicious versions of 314 packages in Alibaba's AntV ecosystem on May 19, 2026. It describes the Mini Shai-Hulud campaign, which uses install hooks and obfuscated Bun scripts to deliver malware and harvest developer credentials. ### Source excerpt The Mini Shai-Hulud npm worm compromised 314 packages in the AntV ecosystem on May 19, 2026 -- including echarts-for-react and timeago.js. ## Mini Shai-Hulud Hits AntV: 300+ Malicious npm Packages Published via Compromised Maintainer Account DevFeed: [Mini Shai-Hulud Hits AntV: 300+ Malicious npm Packages Published via Compromised Maintainer Account]() Original publisher: [Read original article]() Author: Liran Tal Published: 2026-05-18T23:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Data visualization](), [npm packages](), [Malware](), [npm](), [C2](), [Bun](), [JavaScript](), [GitHub]() Tags: [awareness](), [blog](), [c2](), [data-visualization](), [developer](), [devops](), [devrel](), [javascript](), [malware](), [npm-packages](), [payload](), [secrets](), [security](), [snyk-open-source](), [snyk-platform](), [supply-chain](), [supply-chain-security](), [teampcp](), [tokens]() ### AI overview This article analyzes the Mini Shai-Hulud supply-chain attack targeting the AntV data visualization ecosystem through a compromised npm maintainer account. It describes the mass publication of malicious package versions, the embedded Bun payload, credential and secret theft, C2 persistence, and self-propagation using stolen npm tokens. ### Source excerpt A compromised npm maintainer account triggered an automated burst of over 300 malicious package versions across 323 packages in the AntV data visualization ecosystem, part of the ongoing Mini Shai-Hulud supply chain worm campaign. Here's what the malware does, how to detect exposure, and how to respond. ## Uncovering the Shape of Fraud with Cosmos Explorer: Visual Metaphors Behind Millions of Transactions DevFeed: [Uncovering the Shape of Fraud with Cosmos Explorer: Visual Metaphors Behind Millions of Transactions]() Original publisher: [Read original article]() Author: João Bernardo Narciso Published: 2026-04-07T17:24:51Z Content type: article Language: en Sources: [Feedzai]() Topics: [Data visualization](), [data]() Tags: [data](), [data-visualization](), [dataviz](), [decision-making](), [design](), [feedzai](), [fraud](), [fraud-detection](), [patterns](), [research]() ### AI overview Feedzai's Data Visualization Research team is developing Cosmos Explorer, an interface that uses universe-inspired visual metaphors to help analysts examine patterns, trends, outliers, and possible fraud across hundreds of millions or billions of transactions. The project explores how to preserve meaningful details at very large scale while supporting data analysts and data scientists. ### Source excerpt Uncovering the Shape of Fraud with Cosmos Explorer: Visual Metaphors Behind Millions of Transactions The Data Visualization Research team is developing Cosmos Explorer, an interface that leverages universe-related visual metaphors to convey information about the billions of transactions processed by Feedzai. Pedro Cruz, professor at Northeastern University, partnered with Feedzai to bring this idea to life by contributing with his creativity and expertise to solve this challenging visualization problem. https://medium.com/media/1b2ecfadd91d204640462f89fa6ff67f/href When we look out into the universe, we don't just see emptiness. We see an unimaginable scale: billions of galaxies, each containing billions of stars, each a point of light carrying its own story. No single observer can take it all in at once. Yet with the right instruments, patterns emerge: the structure of the cosmos itself becomes visible. In the digital realm, there is another universe just as vast and intricate. Every day, hundreds of millions of events flow through Feedzai's system which assesses them to protect consumers all over the world. Each one is a unique data point (e.g., a purchase, a login, a transfer). Individually, they don't tell us much. Together they form a living universe of behavior that represents the diversity in people's lives. But fraud lurks in everyday transactions, with criminals trying to hide their activities within the sheer volume of transactions. The question is: how can we represent those patterns meaningfully, the normal behaviors and the fraudulent behaviors, the trends and the outliers, to empower data analysts and data scientists in their decision-making processes? The biggest challenge is scale. No one can look at billions of events one by one. Aggregation helps, but it smooths over the details, which often encode the most interesting signals like the faint outlines of fraud or unusual clusters of activity. But what if we could see it all at once? Not just a summa ## February 2026 newsletter DevFeed: [February 2026 newsletter]() Original publisher: [Read original article]() Author: Mark Needham Published: 2026-02-19T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [real-time](), [Data visualization](), [Open Source](), [Streaming](), [anthropic](), [Claude](), [Conversational AI](), [Database](), [Python]() Tags: [anthropic](), [claude](), [clickhouse](), [conversational-ai](), [data](), [data-visualization](), [newsletter](), [python](), [real-time](), [streaming]() ### AI overview The February 2026 ClickHouse newsletter covers the company's Series D funding, its official Kubernetes operator release, data modeling and query optimization guidance, community work using ClickHouse with Claude and LibreChat, and upcoming training sessions and events. ### Source excerpt Welcome to the February 2026 ClickHouse newsletter, which will round up what's happened in real-time data warehouses over the last month. ## From text to charts: a faster way to visualize with ClickStack DevFeed: [From text to charts: a faster way to visualize with ClickStack]() Original publisher: [Read original article]() Author: ClickStack Team Published: 2025-10-22T11:41:42Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [observability](), [Data visualization](), [log management](), [Traces](), [Language models](), [anthropic](), [API keys](), [data](), [Docker Compose](), [Open Source](), [Latency]() Tags: [ai](), [anthropic](), [api](), [clickhouse](), [data-visualization](), [docker](), [latency](), [logs](), [metrics](), [observability](), [open-source](), [root-cause-analysis](), [traces]() ### AI overview ClickStack introduces a text-to-chart feature for observability data. Users describe a desired chart in natural language, and an LLM converts the prompt into a query and visualization for logs, traces, or metrics. The article explains how to enable the feature with an Anthropic API key, try it locally with a Docker image, or use a public demo, while noting that the local image is intended for experimentation rather than production. ### Source excerpt Discover how ClickStack's new text-to-chart feature makes analyzing logs, traces, and metrics effortless - turning plain text into instant observability visualizations that speed up root cause analysis. ## Visualizing Foursquare places with ClickHouse DevFeed: [Visualizing Foursquare places with ClickHouse]() Original publisher: [Read original article]() Author: Alexey Milovidov Published: 2025-05-08T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Data visualization](), [datasets](), [real-time](), [Command-line interface](), [Web]() Tags: [apache](), [clickhouse](), [command-line](), [data-visualization](), [datasets](), [hackathon](), [real-time](), [web]() ### AI overview The article describes a data visualization hackathon project that uses ClickHouse to explore and display a large Foursquare places dataset. It covers previewing and querying the data with clickhouse-local, loading it into ClickHouse, optimizing geographic coordinates and indexes, and adapting a web visualization tool for interactive map analysis. ### Source excerpt Visualizing geographical datasets with ClickHouse in real-time ## Introducing Heroku-Streamlit: Seamless Data Visualization DevFeed: [Introducing Heroku-Streamlit: Seamless Data Visualization]() Original publisher: [Read original article]() Author: Anush DSouza Published: 2025-05-01T08:00:09Z Content type: release Language: en Sources: [Heroku]() Topics: [Heroku](), [Streamlit](), [Template](), [Python](), [web applications](), [Cloud](), [Data visualization](), [Data Science](), [Open Source]() Tags: [ai](), [data-analytics](), [data-visualization](), [deploy](), [deployment](), [developer-tools](), [dockerignore-usage](), [getting-started](), [heroku](), [news](), [open-source](), [prototyping](), [python](), [streamlit](), [web-applications]() ### AI overview Heroku announces Heroku-Streamlit, a ready-to-deploy template for deploying interactive Streamlit data visualization applications on Heroku. The template combines Heroku's cloud platform with Streamlit's Python framework and includes one-click deployment, sample Uber pickup data, customization options, and manual deployment instructions. ### Source excerpt We're excited to announce the release of Heroku-Streamlit, a template that makes deploying interactive data visualization applications on Heroku simpler than ever before. Streamlit is an open-source app framework built for machine learning and data science projects. This Streamlit App brings together Heroku's scalable cloud platform and Streamlit's intuitive Python-based data application framework. Whether you're [...] The post Introducing Heroku-Streamlit: Seamless Data Visualization appeared first on Heroku. ## Enabling Apache ECharts in React for Data Visualization DevFeed: [Enabling Apache ECharts in React for Data Visualization]() Original publisher: [Read original article]() Author: hello@taniarascia.com Published: 2025-03-31T00:00:00Z Content type: tutorial Language: en Sources: [Tania Rascia]() Topics: [Data visualization](), [React](), [Front end](), [JavaScript](), [dashboards]() Tags: [charts](), [dashboards](), [data-visualization](), [front-end](), [javascript](), [react](), [visualization]() ### AI overview A tutorial on creating a small React wrapper for Apache ECharts to build interactive data visualizations, including line, bar, and pie charts. It covers chart initialization, configuration updates, event handling, and resizing. ### Source excerpt Making dashboards with charts and graphs is a pretty common part of the front-end developer experience, as well as deciding which JavaScript... ## Navigate your Turso database with Outerbase DevFeed: [Navigate your Turso database with Outerbase]() Original publisher: [Read original article]() Author: Brandon Strittmatter Published: 2024-06-26T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [Data Management](), [SQLite](), [Data visualization](), [dashboards](), [SQL](), [Artificial Intelligence]() Tags: [ai](), [dashboards](), [data-management](), [data-visualization](), [database](), [sql](), [sqlite](), [turso]() ### AI overview This article explains how to connect a Turso database to Outerbase Studio and use it to view, edit, query, and visualize data. It describes table and schema editing, direct SQL queries, AI querying, dashboards, data visualization, and collaboration features. ### Source excerpt Query, edit, vizualise your Turso Database and more with Outerbase ## Add an interface to your Neon database via Outerbase DevFeed: [Add an interface to your Neon database via Outerbase]() Original publisher: [Read original article]() Author: Brandon Strittmatter Published: 2024-06-07T15:02:35Z Content type: release Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [SQL](), [Data visualization](), [AI Models](), [Data Management](), [dashboards]() Tags: [announce](), [community](), [dashboards](), [data-management](), [data-studio](), [data-visualization](), [database](), [exploration](), [filter](), [generate](), [guide](), [how-to](), [integration](), [interface](), [language](), [models](), [postgres](), [sorting](), [sql](), [team](), [visualization]() ### AI overview The article announces the public availability of the Outerbase integration for Neon. It lets teams connect Neon Postgres databases to Outerbase Data Studio to collaboratively view, edit, query, manage, and visualize data. Outerbase AI can generate SQL queries, schemas, data, and visualizations from natural-language requests. ### Source excerpt We are beyond excited to announce that the Outerbase integration for Neon is now publicly available. This integration enables you to instantly connect your Neon Postgres database to Outerbase's Data Studio and invite your team to view, edit, query, and visualize your data with yo... ## Interactive Data Visualizations with React DevFeed: [Interactive Data Visualizations with React]() Original publisher: [Read original article]() Author: admin Published: 2024-06-02T08:26:04Z Content type: tutorial Language: en Sources: [Posts on Chris Banes]() Topics: [React](), [Data visualization](), [JavaScript](), [User Interfaces]() Tags: [charts](), [charts-and-graphs](), [d3-js](), [data-visualization](), [javascript](), [react](), [uncategorized]() ### AI overview This tutorial explains how React can be used to create interactive data visualizations. It discusses component-based architecture, dynamic updates through the Virtual DOM, performance, flexibility, and the React visualization ecosystem, including Chart.js and D3.js. ### Source excerpt React, the popular JavaScript library for building user interfaces, is a fantastic tool for creating interactive data visualizations. With its component-based architecture and a wealth of libraries at your disposal, React makes it easier than ever to bring your data to life and engage your audience. But why should you choose React for your data [...] ## Real-time Data Visualization: How to build faster dashboards DevFeed: [Real-time Data Visualization: How to build faster dashboards]() Original publisher: [Read original article]() Author: Cameron Archer Published: 2023-08-08T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [Data visualization](), [real-time](), [dashboards]() Tags: [build](), [dashboards](), [data-visualization](), [how-to](), [real-time](), [scalable-analytics-architecture]() ### AI overview This tutorial introduces real-time data visualization, focusing on turning raw data streams into immediate insights and reducing latency in dashboards. ### Source excerpt Real-time data visualization turns raw streams into instant insights. Most tools add too much latency. Here's how to keep it fast. ## Trino Fest nears with an all-star lineup DevFeed: [Trino Fest nears with an all-star lineup]() Original publisher: [Read original article]() Author: Cole Bowden Published: 2023-06-01T00:00:00Z Content type: news Language: en Sources: [Trino Blog]() Topics: [SQL](), [Apache Iceberg](), [Redis](), [Python](), [Caching](), [Latency](), [Data visualization]() Tags: [connectors](), [data](), [data-visualization](), [ecosystem](), [event](), [free](), [latency](), [python](), [redis](), [speakers](), [sql](), [virtual-event]() ### AI overview The article previews the speaker lineup for Trino Fest, a free, two-day virtual event. Featured topics include new data-source connectors, Python tools that integrate with SQL and Trino, Iceberg data lakes, query monitoring, caching, Hudi indexing, and query-latency optimization. ### Source excerpt Trino Fest is just around the corner! We're only two weeks away, and we're excited to share that we've got an incredible speaker lineup with a wide variety of talks about all things Trino. If you're out of the loop, we announced Trino Fest back in April as a two-day, free, virtual event. If you want to attend, see talks live, engage with our speakers in Q&As at the end of each session, you'll need to register, so don't delay, and... Register to attend! With that said, we're also excited to bring you a preview of our exciting speaker lineup. Read on if you'd like to learn more. ## What Power BI is still missing DevFeed: [What Power BI is still missing]() Original publisher: [Read original article]() Published: 2023-03-27T00:00:00Z Content type: opinion Language: en Sources: [Mutt0-ds Notes]() Topics: [Data visualization](), [Git](), [Azure](), [JSON](), [Microsoft](), [GitHub]() Tags: [azure](), [data-visualization](), [git](), [github](), [json](), [microsoft]() ### AI overview An assessment of Power BI at the enterprise level identifies features that remain difficult or unavailable, including basic version control for binary .pbix files. The article describes a workaround using an Azure Pipeline, Tabular Editor 2, JSON metadata, and Git, while noting that charts and visuals are not covered. ### Source excerpt During these months, I had the chance to take a look at Power BI at the enterprise level, juggling advanced requests from hundreds of users... ## Using Server Sent Events to Simplify Real-time Streaming at Scale DevFeed: [Using Server Sent Events to Simplify Real-time Streaming at Scale]() Original publisher: [Read original article]() Author: Bao Nguyen Published: 2022-11-30T14:00:04Z Content type: tutorial Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [real-time](), [Streaming](), [Data visualization](), [Scalability](), [nginx](), [Shopify](), [web applications]() Tags: [data-visualization](), [golang](), [http](), [latency](), [nginx](), [performance](), [real-time](), [scale](), [shopify](), [sse](), [streaming]() ### AI overview This article explains how Shopify used Server-Sent Events (SSE) to simplify the architecture of its BFCM Live Map, a real-time data visualization product. It compares push, polling, and long-polling communication models, then describes implementing a scalable, Nginx-load-balanced SSE server in Golang to improve performance and data latency. ### Source excerpt We walk through how we implemented an SSE server that's scalable and load-balanced to simplify and improve a real-time data visualization application. ## Six Strategies for Making Data Visualizations Accessible, Scalable, and Helpful DevFeed: [Six Strategies for Making Data Visualizations Accessible, Scalable, and Helpful]() Original publisher: [Read original article]() Published: 2022-11-08T13:00:00Z Content type: tutorial Language: en Sources: [Material.io - Material Design]() Topics: [Data visualization](), [Accessibility]() Tags: [accessibility](), [accessible](), [data](), [data-visualization](), [making](), [strategies](), [tips](), [visualization]() ### AI overview The article presents six strategies for making data visualizations accessible, scalable, and helpful. ### Source excerpt Six strategies for making your data visualization accessible, scalable, and helpful ## What's new in Svelte: October 2022 DevFeed: [What's new in Svelte: October 2022]() Original publisher: [Read original article]() Author: Dani Sandoval Published: 2022-10-01T00:00:00Z Content type: article Language: en Sources: [Svelte blog]() Topics: [Svelte](), [Data visualization](), [Extension](), [Accessibility](), [Remix](), [Cloudflare](), [JSON](), [React]() Tags: [accessibility](), [announcement](), [build-performance](), [data-visualization](), [extension](), [react](), [release](), [remix](), [svelte]() ### AI overview This October 2022 update covers new Svelte and SvelteKit features, a two-day Svelte Summit, improvements to the Svelte extension, new accessibility warnings, and educational demonstrations. It also announces the first SvelteKit Release Candidate and highlights updates involving forms, Sverdle, Cloudflare Pages, build performance, Node.js requirements, and generated types. ### Source excerpt There's a bunch of updates this month... from new features in Svelte and SvelteKit to a whole 2-day summit! Plus, the Svelte extension gets some helpful new tools, new accessibility (a11y) warnings, and Tan Li Hau teaches us how to build our own Svelte and a Svelte spreadsheet 😎 What happened at Svelte Summit? A lot! Below you can find all the talks, by timestamp, from each livestream. Bite-size videos of the event will be coming soon to the Svelte Society channel, so be sure to Subscribe, if you haven't already! Day One 12:31 - How to get Svelte adopted at work 33:21 - Animating Data Visualization in Svelte 2:20:36 - Red flags & code smells 2:53:42 - Enhance your DX 4:42:41 - Svelte in UBS' knowledge graph 5:06:42 - How to migrate react libraries to svelte 5:45:27 - DX magic in the world of Svelte 7:25:39 - Data visualizations powered by Svelte 7:59:38 - Partial Hydration in Svelte for Increased Performance 8:20:49 - Building the future, faster Day Two 24:09 - Scrollytell me why: Ain't nothing but a piece of cake 2:02:40 - I told you my dog wouldn't run 2:29:43 - 10Xing Svelte 3:04:56 - Svemix? Re-svmix? Re-svelte?: Bringing Svelte to Remix Router 5:09:39 - Having fun with stores: an interactive demo of Svelte's built in state management library 5:37:06 - When Keeping it Svelte Goes Wrong. An Analysis of Some of the Worst Svelte I Have Ever Coded 7:22:05 - Getting started with Hooks 7:38:14 - Special Announcement* *In the final talk of the summit, Rich Harris announces the first Release Candidate of SvelteKit! With no planned breaking changes left, the team is hard at work squashing bugs and adding the remaining features for 1.0... More SvelteKit Updates use:enhance is the easiest way to progressively enhance a form (Docs, #6633, #6828, #7012) The demo app has been updated to add the Sverdle game, which Rich demoed at Svelte Summit and demonstrates use:enhance (#6979) Cloudflare Pages _routes.json specification is now supported by adapter-cloudflare (#6530) Improve ## Blind people need to be considered more when making data visualizations DevFeed: [Blind people need to be considered more when making data visualizations]() Original publisher: [Read original article]() Author: Johny Cassidy Published: 2022-09-22T00:00:00Z Content type: opinion Language: en Sources: [The A11Y Project]() Topics: [Accessibility](), [Data visualization](), [data]() Tags: [accessibility](), [data](), [data-visualization](), [visualization]() ### AI overview The article argues that the growing use of visual data journalism can exclude blind people and others with visual impairments. It calls for accessible alternatives, such as meaningful text and audio descriptions, so that data visualizations can be understood by everyone. ### Source excerpt Visual data representation is being used more and more in digital newsrooms across the world. The downside, however, is how exclusionary this can be for people with visual impairments. It's clear that visual journalism will play a huge part in the digital future for media outlets. From audience analytics tools measuring the impact of content, to representing complicated data in an easy to digest format, it's easy to see the benefits of such tools and production techniques for creating impactful digital journalism. It's also clear that without a better understanding of how to make visual journalism work for everyone that huge parts of the audience are going to be left behind. In the UK alone, the Royal National Institute of Blind People estimate that around 2 million people are living with some sort of sight loss. Globally, the World Health Organization claim the number is close to 2.2 billion, with that number set to rise dramatically as people continue to age. As a blind journalist, I'm concerned that the increased use of visual data representation without careful and creative thought about accessibility is widening the inaccessibility gap. An example During the COVID pandemic I wasn't easily able to access COVID data represented on digital graphs, and I wasn't alone. A project by MIT researching the problem of data visualization accessibility cited a simple chart from the beginning of the pandemic. The cited chart demonstrated the benefits of mask wearing and social distancing for limiting the spread of the disease. The chart was amplified by many global media outlets, but was missed by millions of blind readers due to lack of meaningful text or audio description. Data journalism's access issues and greater potential In my job as a digital journalist, I'm becoming increasingly aware of the desire to publish more and more impactful visual data journalism. For a lot of people, visual representations of complicated data has the ability to translate data into a format ## Visualizing Supabase Data using Metabase DevFeed: [Visualizing Supabase Data using Metabase]() Original publisher: [Read original article]() Author: Ant Wilson Published: 2022-06-29T07:00:00Z Content type: article Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Data visualization](), [Docker](), [Docker Container](), [PostgreSQL](), [No-code]() Tags: [article](), [blog](), [data](), [data-visualization](), [docker](), [docker-container](), [how-to](), [no-code](), [postgresql]() ### AI overview This tutorial explains how to visualize data stored in Supabase with Metabase. It introduces Metabase as a low-code or no-code tool for creating graphs, pie charts, flow diagrams, and other business-oriented visualizations, then covers connecting Metabase to a Supabase PostgreSQL database and inspecting table insights. ### Source excerpt How to create different kinds of charts out of data stored in Supabase using Metabase. ## Introducing ShopifyQL: Our New Commerce Data Querying Language DevFeed: [Introducing ShopifyQL: Our New Commerce Data Querying Language]() Original publisher: [Read original article]() Author: Ranko Cupovic Published: 2022-06-22T13:00:01Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [Shopify](), [Query (disambiguation)](), [data](), [Data visualization](), [Optimization]() Tags: [coding](), [data](), [data-visualization](), [developers](), [optimization](), [shopify]() ### AI overview Shopify introduces ShopifyQL, an accessible commerce-focused querying language designed to help Shopify Plus merchants explore business data without a data science or coding background. It provides easy-to-learn syntax, one-step visualization, period comparisons, and commerce-specific date functions. ### Source excerpt At Shopify, we recognize the positive impact data-informed decisions have on the growth of a business. But we also recognize that data exploration is gated to those without a data science or coding background. To make it easier for our merchants to inform their decisions with data, we built an accessible, commerce-focused querying language. We call it ShopifyQL. ## Creating a React Library for Consistent Data Visualization DevFeed: [Creating a React Library for Consistent Data Visualization]() Original publisher: [Read original article]() Author: Krystal Campioni Published: 2022-03-15T22:38:56Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [Data visualization](), [Library](), [React](), [Shopify](), [Accessibility](), [User interface design]() Tags: [accessibility](), [components](), [data-visualization](), [library](), [react](), [shopify](), [visualization]() ### AI overview Shopify describes the development of Polaris Viz, a React library intended to make data visualization more consistent across the Shopify admin. The article focuses on the causes of visual and accessibility inconsistencies, and on implementing light and dark themes while allowing library consumers to define their own themes. ### Source excerpt At Shopify, we tell a lot of stories through data visualization. This is the driving force behind business decisions--not only for our merchants, but also for teams within Shopify. With more than 10,000 Shopify employees, though, it is only natural that different teams started using different tools to display data. [Next page]()