data-analysis

Introduction Data analytics play a vital role in decision-making processes for e-commerce. Online market platforms generate massive amounts of data and information about products, their prices, discounts, customer reviews, offers available and, ratings. When properly analysed, this information can be of great use to the sellers, and institutions in understanding customer behaviour, identify produ…

1. Project Introduction and Objective In this project, I used Microsoft Excel and Power Query to clean and analyze a Jumia product dataset and then built an interactive dashboard to summarize pricing, discounts, ratings and customer engagement. The main objective was to turn a small raw e-commerce dataset into useful business information. I wanted the final dashboard to answer practical questions…

This article introduces MIVAIS, a visual analytics (VA) research environment in which people and multiple software agents analyze data together.

The banking industry is entering a new phase where data is emerging as one of the most valuable strategic assets. As artificial intelligence (AI) adoption expands across financial services, banks that can effectively collect, manage and analyse data will gain Read More ... The post Data Becomes a Strategic Competitive Advantage first appeared on Risk Management Association of India .

Deal sourcing used to run almost entirely on relationships. A banker relationship, a scout network, a founder who happened to know the right partner. That model still matters, but it is no longer the whole story. Across private equity, venture capital, and growth equity, investors are increasingly building sourcing pipelines around live market data and […]

In the heart of Thailand’s agricultural heartland, where rice paddies stretch as far as the eye can see, a silent crisis looms: drought. The Chi River Basin, a vital breadbasket for the region, is particularly vulnerable to the whims of monsoon rains

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…