
Artificial Intelligence Regulation: Let’s not regulate mathematics!
AI regulation has accelerated worldwide in 2025, led by the EU’s AI Act and increasing global efforts to ensure safety, fairness and accountability. This article explains why regulating the mathematical inner workings of AI is impractical and why a functional, risk-based, outcome-focused approach is the only path that protects innovation while managing real-world risks.

5 Industries Machine Learning is Disrupting
A quick look at how AI and machine learning are transforming five major industries in 2025: education, healthcare, transportation, finance, and marketing. In the article, you can also read why adopting AI is now essential for businesses to stay competitive.

History of Deep Learning
Explore the evolution of deep learning - from early neural networks in the 1960s to today’s foundation models and generative AI. This updated timeline (2016-2025) covers landmark breakthroughs like AlphaGo, Transformers, BERT, GPT, AlphaFold, and ChatGPT, revealing how deep learning grew from academic theory to a world-shaping technology driving science, creativity, and everyday life.

Data Mining vs Data Harvesting: What’s the Difference and Why It Matters in 2025
As organizations handle more data than ever, it’s easy to confuse data mining with data harvesting. This updated 2025 guide explains the difference: harvesting is about collecting web data, while mining is about analyzing it to uncover insights. Learn how both processes now use AI, real-time analytics, and ethical data practices to turn raw web information into business value — and how Import.io helps companies bridge the two.

Data analysis: What, how, and why to do data analysis for your organization
Being a data-driven business means making decisions based on data, which provides confidence and supports successful actions. Web Data Integration automates the steps of web data analysis, making it quicker, more accurate, and more reliable for businesses to obtain real-time insights for efficient decision-making.

Web Data Integration: Revolutionizing the Way You Work with Web Data
The web has become the largest, fastest-changing data source on the planet — a living ecosystem of signals, prices, reviews, trends, and insights.From finance and retail to travel and research, organizations rely on web data to understand markets, optimize operations, and outpace competitors.

Eighteen Graphs About the Death Penalty
This article explores how the death penalty is applied in the United States using 18 detailed graphs drawn from data accessed via import.io and the Death Penalty Information Center. It’s divided into three parts: opposition to the death penalty (9 graphs), the deterrence argument (5 graphs), and broader trends & public opinion (4 graphs). Through visualisations covering geography, race, cost, innocence exonerations, homicide rates and public sentiment, the piece provides a data-driven look at a complex issue.

Project Policy Wins the SVC2UK Startup Weekend Competition
Project Policy won the SVC2UK Startup Weekend finals with a data-driven policy tool built using import.io. Formed at Startup Weekend Cambridge, the team impressed judges at Google Campus London and now advances to the Global Startup Battle. Runner-up Hands Free Cook Book also used import.io, highlighting the strong innovation and talent across the event.

Unlock the Secrets of Data Sourcing: What Is Data Sourcing
Data sourcing is a critical process for data scientists and analysts, as it enables them to access the most relevant datasets for their projects. Learn how to source data efficiently and safely, potential challenges, and best practices for successful results.

Unlock the Secrets of Data Extraction of News Articles
Data extraction of news articles is an increasingly important task for data scientists and analysts. With the rapid growth in online content, it's becoming more critical to extract structured information from unstructured sources like news articles.

What is data aggregation? Examples of data aggregation by industry.
In today’s data-driven world, the importance of data aggregation cannot be overstated. By gathering data from multiple sources and presenting it in a summarized format, organizations can gain insights more efficiently and make more informed decisions.

What is data, and why is it important?
Whichever industry you work in, or whatever your interests, you will almost certainly have come across a story about how “data” is changing the face of our world. The collection and analysis of data play a crucial role in making informed decisions and driving insights, with data scientists being highly sought after for their expertise in processing and interpreting data.

What is data normalization and why is it important?
In the ongoing effort to use big data, you may have come across the term “data normalization.” Understanding this term and knowing why it is so important to today's business operations can give a company a real advantage as they go further in-depth with big data in the future.

Key Insights to Optimize eCommerce Pricing
Monitoring channel pricing to ensure consistency is crucial since consumers are able to identify and take advantage of pricing irregularities more quickly and easily than before. A consistent price perception is critical. Inconsistent pricing can damage a brand’s reputation, reduce shopper loyalty and ultimately sales.

Why owning a brand’s presence online means understanding brand comparisons
This article explains why brands must understand how they’re compared to competitors across online retail sites. From search results and brand pages to product suggestions and ads, these comparisons shape consumer perception and purchase decisions. The article highlights key comparison areas and emphasizes the need for continuous monitoring to protect and strengthen a brand’s online presence.

Import.io twice as successful than web scraping at extracting complete e-commerce product data
The main web data quality problem that they were facing was that their web scraping software was collecting incomplete web data from each product page more than half of the time. Different product-data field values would be missing from nearly 60% of all product records.

2023 Guide: Scrape Data From Any eCommerce Website
The increasing volume of online data is hastening business adoption of data-driven decision-making strategies, and it has been estimated that data-driven companies are 19 times more likely to be profitable and 52% better at understanding their customers.

Why do businesses scrape customer reviews?
The scraping of customer reviews can be a useful source of data for e-commerce data extraction, yielding in-depth information that can enable detailed sentiment analysis and drive marketing decision-making. This can be accomplished by scraping customer reviews.










