data-analysis

Ask any data analyst what tool they touched first, and there's a good chance the answer is Excel. Despite the rise of Python, R, and cloud-based BI platforms, Excel hasn't gone anywhere. It's still sitting at the center of how businesses actually handle data day to day, and understanding why says a lot about what data analysis really looks like outside of a classroom. Why Excel Still Matters Part…

A survey of over 700 professionals examines how visual and physical AI teams build systems, why models fail, and where data work drives production. Download this free whitepaper now!

Argonne's DONUT, a machine learning tool, delivers real-time X-ray data analysis at the Advanced Photon Source, giving scientists faster insights into material structures and accelerating discovery in advanced materials research.

Exploratory data analysis , or EDA, is the habit of looking at your data before you compute anything from it. This guide covers what to look at, the research showing why it is not optional, and what it looks like on real projects you can open and read. It exists to prevent one specific failure, and that failure has nothing to do with math. An analyst computes an answer from data they never looked…

This report examines R&D waste and how AI adoption has outpaced the intelligence needed to make consequential decisions well. What Attendees will Learn Where R&D budget is lost. More than a third of organizations spend 25 to 40 percent of their R&D budget on projects that never reach market. Why projects fail late. Almost half of teams estimate over one million dollars in wasted investment for ea…

Discover five of the best AI tools for data analysis that can clean data, write code, create visualizations, and generate insights faster.

The role of scientists has changed from being active observers to data analysts. The limitations on scientific discovery have moved away from the tools that were used to do so and toward algorithms, where AI is crucial.

Author : Leo, Technical Lead at Pangolinfo Tags : amazon python api mcp web-scraping data-analysis Reading time : ~12 minutes TL;DR This tutorial walks through building a complete Amazon competitor research system using Python and the Pangolinfo API. You'll learn the 5-step IBADM framework (Identify → Baseline → Analyze → Differentiate → Monitor) and get production-ready code you can run today. W…

Over the past few weeks, I’ve been diving into the fundamentals of data analysis. It’s been an eye opening experience, and I’d like to share some of the key lessons I’ve learned so far. 1. Getting Started with Data Analysis The first step was understanding what data analysis really means and what a data analyst does. I discovered that being an analyst isn’t just about crunching numbers it’s about…

Data is everywhere, but raw data alone has little value. The real power lies in transforming that data into meaningful insights that support better decisions. Whether you're a student working on a final-year project, a researcher analyzing survey results, or a beginner entering the field of data science, understanding the data analysis workflow is an essential skill. In this article, I'll walk th…

Check out this practical list of Python projects covering AI automation, machine learning, APIs, dashboards, data analysis, and portfolio-ready apps, with guides, demos, repositories, and datasets.

The system moves high-speed detector data directly to GPUs , allowing scientists to examine more information before it is filtered out or sent for storage. NVIDIA DAQIRI connects high-speed scientific instruments and sensors directly with GPU-powered computing systems for real-time data processing. Image credit: NVIDIA NVIDIA has introduced DAQIRI, a high-speed data system designed to process inf…

“Real data analysis starts with Python or SQL.” That’s what I believed too until I spent weeks working on messy, real-world datasets in Excel. Not toy datasets. Not tutorial data. Actual transaction logs, customer records, and reporting data with inconsistencies, duplicates and missing values. And surprisingly? Excel handled most of it better than expected. Most people underestimate Excel so much…

IntroductionThis study develops a machine learning-based framework for disaster risk assessment, economic loss estimation, and insurance claims prediction using multi-source environmental, socioeconomic, and temporal data. The aim is to improve predictive accuracy and decision-making in insurance and disaster management systems.MethodsA dataset of 68,485 disaster records (1953–2025) covering 10 d…

Before I thought Excel was just something accountants use to make tables look neat. I was wrong — quite embarrassingly wrong, actually. This changed how I see spreadsheets entirely. Excel isn't a glorified notepad. It's a proper analytical tool that businesses use daily to make real decisions. Let me share what I've learned and how it connects to the real world. What even is Excel? Microsoft Exce…

BackgroundTranexamic acid (TXA) is a widely used antifibrinolytic agent for the management of hemorrhagic disorders and has increasingly been investigated for the treatment of intracerebral hemorrhage (ICH). However, TXA-associated adverse drug events (ADEs), particularly neurological complications, remain insufficiently characterized, despite their association with unfavorable neurological outco…