data visualization
data visualization on Beyond Market Intelligence: a running collection of 10 stories we have gathered and hand-picked because they are worth your time. Every post here touches on data visualization in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around data visualization, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Presentation: Beyond Line Charts: Why Some Diversity in Telemetry Visualization Is Long Overdue
For years, system observability has relied too heavily on line charts, obscuring critical insights. Yao Yue, drawing on 15 years of experience operating large-scale systems, argues it's time for a change. This presentation, "Beyond Line Charts," explores the fundamental limitations of this default visualization and demonstrates how engineering leaders can transform telemetry data to directly address capacity, latency, and fleet-sizing challenges.
This former PG&E engineer is building a ‘Google Maps for the underground’
Navigating underground infrastructure—pipes, cables, and conduits—is notoriously complex, a challenge one former PG&E engineer is tackling head-on. His startup is building a “Google Maps for the underground,” providing unprecedented clarity for utility and construction work. Recently, the company secured a $26 million Series A to expand its customer base and streamline processes, reducing red tape and improving efficiency. This innovation echoes the rapid growth seen in the AI space, as highlighted by Instinct’s recent $350 million raise.
Rethinking Data Visualisation: A UX Approach To Dashboards That Actually Drives Decisions
Data visualization often falls short of driving meaningful decisions, hampered by a disconnect between data and design. Rethinking Data Visualisation explores a transformative approach: applying structured UX thinking to dashboards and data presentations. Meriem Benhabiles guides you through a process, from initial questioning to impactful insight delivery. This isn't about aesthetics; it's about ensuring data truly informs action. For a deeper dive into related AI challenges, explore "How Does a RAG Reranker Really Work?" and discover enterprise document intelligence.
What font is everyone using?
## What Font is Everyone Using? – And Why? The question of font choice sparks surprisingly passionate debate! We’re exploring the practical fonts users rely on for spreadsheets, and the reasons behind those selections. Do you tailor your font based on data density or visual clarity? What are your go-to options for optimal readability and workflow? This discussion, initiated by /u/DownRUpLYB, delves into the often-overlooked importance of typography within spreadsheet environments.
How PGSimCity Turns PostgreSQL Complexity Into a Virtual City 3D Simulation
Backend developers and site reliability engineers face a persistent challenge: grasping the intricacies of PostgreSQL. Nikolay Samokhvalov’s PGSimCity offers a transformative solution. This open-source tool visualizes PostgreSQL mechanics as an interactive 3D spatial simulation, accessible directly in the browser. Explore how database architecture comes to life, simplifying SQL and kernel execution dynamics. Available on GitHub, PGSimCity empowers a deeper understanding through engaging visuals.
Struggling with creating a stack? bar? chart
Visualizing "before and after" questionnaire results can be tricky! Many users find accurately representing data for stacked or bar charts in Excel challenging. We understand the frustration of getting those headlines and values just right. To achieve the diagram you envision, focus on structuring your Excel data with clear labels and corresponding values for each category—before and after. For more complex data manipulation, consider exploring techniques like those discussed in our article, "I created a triple nested XLOOKUP formula...
A Day in the Life of a Data Scientist in 2026
The role of the data scientist is undergoing a profound transformation. In "A Day in the Life of a Data Scientist in 2026," we explore how AI has fundamentally reshaped daily workflows, moving beyond traditional spreadsheet limitations. Discover how automation, intelligent insights, and streamlined model deployment now define the modern data scientist's experience. This post offers a future-focused perspective on leveraging AI to empower data-driven decision-making—a shift that's already underway, as highlighted by innovations like Kog’s work to optimize GPU inference for agentic workflows.
Matplotlib vs Plotly: Which Python Chart Tool Should You Choose?
Navigating the world of Python charting can feel overwhelming. Choosing between Matplotlib and Plotly depends on your goals. Matplotlib remains a reliable choice for generating static, publication-ready plots—a foundational tool for many data scientists. However, Plotly excels in interactive data exploration, enabling dynamic visualizations and user engagement. For those seeking to build data agents and conversational interfaces, as explored in "I Built an AI Data Agent," Plotly’s interactivity offers a significant advantage. Discover which tool best empowers your data journey.
What to consider when creating waterfall charts
Waterfall charts offer a clear, visual breakdown of how an initial value increases or decreases through a series of steps. When crafting these charts, consider the order of your data—it matters! Prioritize clarity by using distinct colors for each segment and ensuring labels are concise and easily understood. A well-constructed waterfall chart effectively communicates complex data trends at a glance. For related insights on navigating the evolving landscape of AI-generated content, explore our recent article, "LinkedIn adds a button to report AI-generated ‘slop’."
![Follow up: GPT-2's vocabulary as a hyperbolic tree — 32,070 tokens in a Poincaré ball you can fly through [P]](https://preview.redd.it/o6l1c96lo6eh1.png?width=640&crop=smart&auto=webp&s=92447206205a44b4f473a41cc8557c245d73a7d0)
Follow up: GPT-2's vocabulary as a hyperbolic tree — 32,070 tokens in a Poincaré ball you can fly through [P]
Explore the fascinating architecture of GPT-2's vocabulary with a unique visualization: a hyperbolic tree containing 32,070 tokens rendered within a Poincaré ball. This interactive experience, running directly on your phone, allows you to navigate the relationships between tokens through intuitive drag, pinch, and tap interactions. The structure reveals a natural "forest" of interconnected elements, best represented in hyperbolic space—a design that elegantly accommodates the vocabulary's complex similarity structure. Discover more on this topic with our article, "Kimi: Threat or menace?".