Altosight | AI Custom Web Scraping Data

✦ Altosight provides global web scraping data services with AI-powered technology that bypasses CAPTCHAs, blocking mechanisms, and handles dynamic content.

We extract data from marketplaces like Amazon, aggregators, e-commerce, and real estate websites, ensuring comprehensive and accurate results.

✦ Our solution offers free unlimited data points across any project, with no additional setup costs.

We deliver data through flexible methods such as API, CSV, JSON, and FTP, all at no extra charge.

― Key Use Cases ―

➤ Price Monitoring & Repricing Solutions

🔹 Automatic repricing, AI-driven repricing, and custom repricing rules 🔹 Receive price suggestions via API or CSV to stay competitive 🔹 Track competitors in real-time or at scheduled intervals

➤ E-commerce Optimization

🔹 Extract product prices, reviews, ratings, images, and trends 🔹 Identify trending products and enhance your e-commerce strategy 🔹 Build dropshipping tools or marketplace optimization platforms with our data

➤ Product Assortment Analysis

🔹 Extract the entire product catalog from competitor websites 🔹 Analyze product assortment to refine your own offerings and identify gaps 🔹 Understand competitor strategies and optimize your product lineup

➤ Marketplaces & Aggregators

🔹 Crawl entire product categories and track best-sellers 🔹 Monitor position changes across categories 🔹 Identify which eRetailers sell specific brands and which SKUs for better market analysis

➤ Business Website Data

🔹 Extract detailed company profiles, including financial statements, key personnel, industry reports, and market trends, enabling in-depth competitor and market analysis

🔹 Collect customer reviews and ratings from business websites to analyze brand sentiment and product performance, helping businesses refine their strategies

➤ Domain Name Data

🔹 Access comprehensive data, including domain registration details, ownership information, expiration dates, and contact information. Ideal for market research, brand monitoring, lead generation, and cybersecurity efforts

➤ Real Estate Data

🔹 Access property listings, prices, and availability 🔹 Analyze trends and opportunities for investment or sales strategies

― Data Collection & Quality ―

► Publicly Sourced Data: Altosight collects web scraping data from publicly available websites, online platforms, and industry-specific aggregators

► AI-Powered Scraping: Our technology handles dynamic content, JavaScript-heavy sites, and pagination, ensuring complete data extraction

► High Data Quality: We clean and structure unstructured data, ensuring it is reliable, accurate, and delivered in formats such as API, CSV, JSON, and more

► Industry Coverage: We serve industries including e-commerce, real estate, travel, finance, and more. Our solution supports use cases like market research, competitive analysis, and business intelligence

► Bulk Data Extraction: We support large-scale data extraction from multiple websites, allowing you to gather millions of data points across industries in a single project

► Scalable Infrastructure: Our platform is built to scale with your needs, allowing seamless extraction for projects of any size, from small pilot projects to ongoing, large-scale data extraction

― Why Choose Altosight? ―

✔ Unlimited Data Points: Altosight offers unlimited free attributes, meaning you can extract as many data points from a page as you need without extra charges

✔ Proprietary Anti-Blocking Technology: Altosight utilizes proprietary techniques to bypass blocking mechanisms, including CAPTCHAs, Cloudflare, and other obstacles. This ensures uninterrupted access to data, no matter how complex the target websites are

✔ Flexible Across Industries: Our crawlers easily adapt across industries, including e-commerce, real estate, finance, and more. We offer customized data solutions tailored to specific needs

✔ GDPR & CCPA Compliance: Your data is handled securely and ethically, ensuring compliance with GDPR, CCPA and other regulations

✔ No Setup or Infrastructure Costs: Start scraping without worrying about additional costs. We provide a hassle-free experience with fast project deployment

✔ Free Data Delivery Methods: Receive your data via API, CSV, JSON, or FTP at no extra charge. We ensure seamless integration with your systems

✔ Fast Support: Our team is always available via phone and email, resolving over 90% of support tickets within the same day

― Custom Projects & Real-Time Data ―

✦ Tailored Solutions: Every business has unique needs, which is why Altosight offers custom data projects. Contact us for a feasibility analysis, and we’ll design a solution that fits your goals

✦ Real-Time Data: Whether you need real-time data delivery or scheduled updates, we provide the flexibility to receive data when you need it. Track price changes, monitor product trends, or gather...

Context

Data set containing Tweets captured during the Nintendo E3 2018 Conference.

Content

All Twitter APIs that return Tweets provide that data encoded using JavaScript Object Notation (JSON). JSON is based on key-value pairs, with named attributes and associated values. The JSON file include the following objects and attributes:

• Tweet - Tweets are the basic atomic building block of all things Twitter. The Tweet object has a long list of ‘root-level’ attributes, including fundamental attributes such as id, created_at, and text. Tweet child objects include user, entities, and extended_entities. Tweets that are geo-tagged will have a place child object.

  • User - Contains public Twitter account metadata and describes the author of the Tweet with attributes as name, description, followers_count, friends_count, etc.

  • Entities - Provide metadata and additional contextual information about content posted on Twitter. The entities section provides arrays of common things included in Tweets: hashtags, user mentions, links, stock tickers (symbols), Twitter polls, and attached media.

  • Extended Entities - All Tweets with attached photos, videos and animated GIFs will include an extended_entities JSON object.

  • Places - Tweets can be associated with a location, generating a Tweet that has been ‘geo-tagged.’

More information here.

Acknowledgements

I used the filterStream() function to open a connection to Twitter's Streaming API, using the keywords #NintendoE3 and #NintendoDirect. The capture started on Tuesday, June 12th 04:00 am UCT and finished on Tuesday, June 12th 05:00 am UCT.

Inspiration

• Time analysis
• Try text mining!
• Cross-language differences in Twitter
• Use this data to produce a sentiment analysis
• Twitter geolocation
• Network analysis: graph theory, metrics and properties of the network, community detection, network visualization, etc.

The js-tweaks extension for CKAN offers a collection of JavaScript scripts, macros, and helpers aimed at streamlining common tasks and user interactions within a CKAN instance. It primarily focuses on enriching the user interface through simple modifications that can improve the overall usability of the platform. By providing readily available tools to implement features such as tooltips, this extension facilitates a more interactive and informative environment for CKAN users. Key Features: Tooltip Implementation: Allows for the rapid addition of basic tooltips to elements on a CKAN page by simply adding the data-tooltip="text" attribute. Bootstrap Tooltip Compatibility: Supports the use of Bootstrap's tooltip functionality for more advanced tooltip implementations and customization using standard Bootstrap attributes (data-toggle="tooltip" data-placement="top" title="Tooltip on top"). Customizable UI: Provides a foundation for further UI enhancements through the inclusion of JavaScript scripts and macros, which is meant to allow for targeted tweaks to match specific user needs or preferences. Simplified Routing: The goal is to make daily routing easier. Technical Integration: The js-tweaks extension is enabled by adding js-tweaks to the ckan.plugins setting in the CKAN configuration file (/etc/ckan/default/ckan.ini by default). After modifying the configuration, restarting CKAN instance is necessary to apply the configurations to enable the modifications offered by the extension. Benefits & Impact: Implementing the js-tweaks extension enables CKAN administrators to quickly implement enhancements to the user interface and routing within the overall platform, such as by adding tooltips or building on the JS, improving user experience without extensive coding or modification to the core CKAN system. While the provided documentation is limited, it aims to reduce complexity and make CKAN interfaces intuitive.

Context

Data set containing Tweets captured during the 2018 UEFA Champions League Final between Real Madrid and Liverpool.

Content

All Twitter APIs that return Tweets provide that data encoded using JavaScript Object Notation (JSON). JSON is based on key-value pairs, with named attributes and associated values. The JSON file include the following objects and attributes:

• Tweet - Tweets are the basic atomic building block of all things Twitter. The Tweet object has a long list of ‘root-level’ attributes, including fundamental attributes such as id, created_at, and text. Tweet child objects include user, entities, and extended_entities. Tweets that are geo-tagged will have a place child object.

  • User - Contains public Twitter account metadata and describes the author of the Tweet with attributes as name, description, followers_count, friends_count, etc.

  • Entities - Provide metadata and additional contextual information about content posted on Twitter. The entities section provides arrays of common things included in Tweets: hashtags, user mentions, links, stock tickers (symbols), Twitter polls, and attached media.

  • Extended Entities - All Tweets with attached photos, videos and animated GIFs will include an extended_entities JSON object.

  • Places - Tweets can be associated with a location, generating a Tweet that has been ‘geo-tagged.’

More information here.

Acknowledgements

I used the filterStream() function to open a connection to Twitter's Streaming API, using the keyword #UCLFinal. The capture started on Saturday, May 27th 6:45 pm UCT (beginning of the match) and finished on Saturday, May 27th 8:45 pm UCT.

Inspiration

• Time analysis
• Try text mining!
• Cross-language differences in Twitter
• Use this data to produce a sentiment analysis
• Twitter geolocation
• Network analysis: graph theory, metrics and properties of the network, community detection, network visualization, etc.

This is a dataset of GitHub repositories that were tagged with Jest, for JavaScript and TypeScript languages, that used Snapshot Testing. Information on all repositories is available in the file "0_Snapshot Testing Dataset.xlsx" (named to be the very first file). Most files represent the repository packed in targz format as "

The description of the attributes from the DependentVariable class in version 1.0 of the CSD model.

Mapping of CSD model attribute values to JSON serialized values.