data
data on Beyond Market Intelligence: a running collection of 75 stories we have gathered and hand-picked because they are worth your time. Every post here touches on data 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, 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.
AI data giant Alation confirms cyberattack
Alation, a leading provider of data search and AI solutions, has confirmed unauthorized access to its systems following an incident on Tuesday. The company is actively investigating the breach and working to secure its environment. This event highlights the evolving cybersecurity landscape and underscores the importance of robust data protection measures. For further insights into related AI infrastructure developments, explore our article on Ramp’s new AI model routing service, Router. We will continue to provide updates as more information becomes available.
Harper Argues Against the Multi-System Stack and Releases 5.2
Harper is challenging the status quo of multi-system architectures, advocating for a single-runtime database platform that unifies application code and data. Recent benchmarks demonstrate significantly improved performance on live, personalized-data workloads compared to Vercel-based stacks. Version 5.2 further solidifies this approach, introducing a new record cache and increased throughput per node. Discover how Harper’s streamlined architecture empowers data-driven applications—for context, explore our analysis of Next.js 16.3’s recent performance improvements.
Trying to count number of times that appear in list
Analyzing data across multiple sheets can be streamlined with the right approach. You're seeking to count occurrences of job titles from Sheet 1 within Sheet 2, matching them to corresponding names. This requires a formula that iterates through Sheet 1’s column, then counts matches in Sheet 2. Explore leveraging functions like `COUNTIF` combined with `VLOOKUP` or `INDEX/MATCH` for accurate results. For troubleshooting similar spreadsheet challenges, our article on "#SPILL! errors" offers valuable insights into resolving unpredictable errors.
Add up bills in date range using only the day
Need to automate bill aggregation in your budget spreadsheet? You're aiming to pull bill amounts based on due dates falling within a weekly timeframe, specifically between a Friday payday and the following Friday. While `SUMIF` can be useful, a more tailored formula is needed to achieve this. Explore leveraging `SUMIFS` to filter by both the day of the month and your payday reference date.
Floating plot on evergrowing spreadsheet possible?
Many spreadsheet users face the frustration of plots becoming detached from the data they summarize as tables grow. /u/orbitolinid highlights this challenge, specifically noting the need for a "floating" plot within Microsoft Excel Professional Plus 2024 on a 14" laptop screen, where daily data additions necessitate constant manual adjustments. This common workflow limitation underscores the need for more adaptive data visualization tools.
Making the Knowledge Layer a Graph You Actually Traverse
Traditional knowledge layers often falter when retrieval quality hinges on precise question phrasing. We're shifting that paradigm. Our approach reimagines the knowledge layer as a traversable graph, ensuring consistent results regardless of query wording. This involves rebuilding with graph traversal on every query, incorporating bitemporal edges for nuanced context, and employing a two-threshold entity resolution process.
Excel + Power Query and Power Automate
Automating data refresh between Salesforce, Power Query, and Excel unlocks significant productivity gains. You've correctly identified that `workbook.refreshAllDataConnections()` within an Office Script can trigger Power Query refreshes, as demonstrated by your pivot table update. To reliably refresh data imported via Power Query using Power Automate, ensure your Excel table’s properties are configured to “Refresh data when opening the file,” disabling background refresh. This forces a refresh upon script execution.
Creating groups based on priorities
Here's a concise introduction, adhering to the brand voice guidelines and incorporating the requested elements: "Organizing students into activity groups based on their priorities presents a common challenge—and a prime opportunity for automation. As one educator discovered while planning their annual theme-week, manual team creation can be time-consuming and potentially less optimal. Leveraging AI-native spreadsheet technology allows for a more efficient and equitable distribution, particularly when activities have varying group size constraints.
Sorting column content separated by comma
Migrating from Google Sheets to Excel? Encountering a unique sorting challenge? This function—`=sort(unique(trim(tocol(iferror(split(Log!J33:J,",")),1))))`—efficiently extracts and alphabetizes comma-separated values within a column. It's a powerful technique for consolidating data, ensuring each item is uniquely represented and neatly ordered. If you're managing large datasets, similar to the approach described in "How to keep a large data set on one sheet that prints out multiple pages?", this method can be invaluable. Explore this solution to streamline your Excel workflows and unlock greater data clarity.
Looking for 1 teammate — RealPDE Competition (NeurIPS 2026)[D]
Ready to tackle a challenging AI problem? The RealPDE Competition (NeurIPS 2026) invites skilled machine learning practitioners to join a team of up to three and explore innovative solutions for fluid dynamics data – real PIV and CFD – across Sim2Real and LTTTA tracks. This competition offers a unique opportunity to transform your data handling skills. Interested? DM the poster to join. Registration closes August 20th. Learn more and register here: https://realpdecompetition.github.io.
AI isn’t close to curing cancer. This startup says it knows what it will take.
The pursuit of AI-driven medical breakthroughs often overstates near-term possibilities. While a cure for cancer remains distant, a new startup is focusing on a fundamental truth: it’s the data, stupid. Their approach prioritizes meticulous data curation and intelligent modeling—a pragmatic strategy for unlocking insights hidden within complex biological datasets. This emphasis on foundational data practices represents a crucial shift, mirroring the innovative techniques explored in our recent piece, "Trained an diffusion model that runs on 264KB of RAM."
Amazon, which started off selling books, is destroying rare texts to train AI
Amazon’s expansion into AI is raising critical questions about data sourcing. Reports indicate the company is destroying rare books—incredibly valuable resources for training Large Language Models—to feed its AI systems. This practice highlights a growing tension: while vast datasets are essential for LLM development, the reliance on irreplaceable historical materials presents a significant ethical and preservation concern.
Grab Cuts Mechanical Analytics Work From 44% to 30% with AI Agents
Grab has demonstrably transformed its analytics workflows with AI agents, achieving a significant 30% reduction in mechanical analyst work since February – a 44% decrease. This progress stems from a powerful combination of agent autonomy, certified data, contextual awareness, and crucial human oversight. Self-service analytics are increasingly handling routine metric, data, and SQL requests, freeing analysts for higher-value tasks. Interested in the underlying architectural principles? Explore "Agentic Fitness Functions" for a deeper dive into extending evolutionary architecture.
5 Python Libraries That Make Data Cleaning More Enjoyable
Data cleaning doesn’t have to be a chore. This article introduces five Python libraries designed to transform tedious data preparation into an expressive and genuinely enjoyable process. We've compiled a list of tools that empower you to streamline workflows and unlock deeper insights from your data. Discover how these libraries can simplify complex tasks and accelerate your analysis. For those working with image classification, you might find our accompanying dataset, "Starfield Fauna," a valuable resource for practical application.
How to Shine as a Data Scientist in the Vibe Coding Era
The rise of AI coding tools like those explored in "How to Install Codex CLI" signals a significant shift for data scientists. Coding proficiency is increasingly becoming a commodity; the future belongs to those who leverage these tools strategically. This post outlines how to thrive in this "Vibe Coding Era," focusing on higher-level skills like problem framing, insightful analysis, and communicating data-driven narratives. Discover how to evolve beyond coding and become the indispensable data scientist of tomorrow.
I'm looking to pull text from schematics and put the into an excel spreadsheet to create a wiring checklist.
Extracting cable IDs from wiring schematics—a common challenge—can be streamlined for creating efficient wiring checklists. You’re already utilizing Kofax Power PDF, a solid starting point. However, refining your extraction process beyond the "Looks Like" feature is key. Focus on leveraging pattern recognition to isolate those specific 5-digit or "5-digit-C" identifiers. For further exploration of data visualization related to your extracted data, consider our article "Struggling with creating a stack? bar? chart," which addresses similar data arrangement challenges.
How to get a table to match the number of rows, and row order, of a parent table
Need to streamline your data management? When adding new expense types to your parent table, automatically populate corresponding rows in linked tables—saving valuable time. This approach ensures consistent data structure and eliminates manual row insertion. It’s a powerful way to maintain data integrity and workflow efficiency. Discover how to configure this feature, mirroring your parent table's growth across related sheets. For troubleshooting formula errors that might arise, see our article, "Pls help - Need to fix formula with Spill Error," for helpful guidance.
How do I use the green square/fill handle without a mouse?
Navigating Excel’s autofill feature without a mouse can streamline your workflow. The green fill handle, typically double-clicked to extend formulas or data down a column, presents a challenge when mouse access is limited. Currently, Excel lacks a dedicated keyboard shortcut to replicate this double-click action directly.
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...
Vlookups and filtered tables
Navigating shared names in your municipality data is a common challenge. While Excel doesn’t directly support compound references within VLOOKUP, your instinct to filter is sound. Creating separate, filtered tables—village, town, city, county—is the most reliable approach to ensure accurate lookups. This strategy isolates data, preventing mismatched results. For those seeking broader automation strategies, explore "Is it possible to automate data input from multiple workbooks," which delves into streamlining data handling across spreadsheets.
Link QR code to a specific cell?
Linking a QR code directly to a specific cell in a spreadsheet—a surprisingly practical need for taxonomists and others—is indeed possible, though often perceived as requiring expensive software. Fortunately, accessible solutions exist. You can leverage scripting or add-ons within spreadsheet platforms to create this functionality. Essentially, the QR code would trigger a URL that, when scanned, automatically opens your spreadsheet and highlights the designated cell, ready for data entry.
Standard derivation of the last three data in a column
Measuring consistency in your hobby group's results is a smart approach. To calculate the standard deviation of the last three data points in a column, the STDEV.P function is indeed the right tool. Your attempt using INDEX and COUNTA is a common hurdle—Excel’s formula complexity can be frustrating. A more straightforward approach involves using the OFFSET function. For example, `=STDEV.P(OFFSET([LA], COUNTA([LA])-3, 0, 3, 1))` will directly compute the standard deviation for the last three entries in column [LA].
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.
Amazon will train on Twitch streamers’ content by default, unless they opt out
Amazon will now leverage Twitch streamer content for AI training by default, a decision underscored by Twitch CPO Mike Minton’s statement that an opt-in system would see minimal adoption. This shift reflects a commitment to rapidly advancing AI capabilities, though it raises considerations around creator consent and data usage. Users retain the ability to opt out, ensuring control over their content.