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WS · Business Process Automation & AI

Web Scraping & Data Mining

Data collected from websites, APIs, portals and files, then cleaned, normalized and loaded where you need it. Built in Python with Selenium where a real browser is required, run on a schedule, and monitored so you hear about it when a source changes.

Start a project 5–20 business days
Web Scraping & Data Mining
What we cover

Web Scraping & Data Mining services

27 services
  1. 01

    Web Scraping & Web Data Extraction

    Structured extraction of data from websites that offer no export or API.

  2. 02

    Python Web Scraping

    Scrapers written in Python, version-controlled and handed over as source.

  3. 03

    Automated Website Data Collection

    Recurring collection runs that keep a dataset current without manual gathering.

  4. 04

    API Data Extraction

    Pulling data from REST and other APIs, with pagination, rate limits and auth handled.

  5. 05

    Dynamic Website Scraping

    Extraction from sites that build their content in the browser with JavaScript.

  6. 06

    Selenium Browser Automation

    Driving a real browser for sites that require login, interaction or navigation steps.

  7. 07

    Large-Scale Data Scraping

    High-volume collection designed for throughput, retries and partial-failure recovery.

  8. 08

    Scheduled Web Scraping

    Collection on a fixed schedule, with run history and alerting.

  9. 09

    Price & Market Data Scraping

    Ongoing capture of pricing and market data from published sources.

  10. 10

    Commodity Price Data Collection

    Commodity quotes and reference prices gathered from public and subscribed sources.

  11. 11

    Competitor Price Monitoring

    Tracking competitor pricing over time and flagging movements.

  12. 12

    Product & Pricing Data Extraction

    Catalog, specification and price data pulled into a structured format.

  13. 13

    Market Intelligence Data Collection

    Assembling market data from multiple sources into one comparable dataset.

  14. 14

    Public / Government Data Extraction

    Collection from public registers, portals and open-data publications.

  15. 15

    PDF, CSV, Excel, JSON & XML Data Extraction

    Reading structured and semi-structured files into usable records.

  16. 16

    Data Mining & Data Collection

    Locating, acquiring and consolidating data from across many sources.

  17. 17

    Data Cleaning & Transformation

    Correcting, standardizing and reshaping raw data so it can be relied on.

  18. 18

    Data Mapping & Normalization

    Reconciling different source schemas into one consistent model.

  19. 19

    Data Deduplication

    Identifying and resolving duplicate records across and within sources.

  20. 20

    ETL Pipeline Development

    Extract, transform and load pipelines built to run unattended.

  21. 21

    Web-to-Database Automation

    Scraped data written directly into your database on each run.

  22. 22

    API-to-Database Automation

    API responses parsed and persisted into your own data store.

  23. 23

    MongoDB / MySQL Data Processing

    Ingestion, querying and processing against MongoDB or MySQL.

  24. 24

    Data Migration & Synchronization

    Moving data between systems, or keeping two systems in step.

  25. 25

    Automated Data Monitoring

    Continuous checks on the data a process depends on.

  26. 26

    Data Availability & Freshness Monitoring

    Alerts when an expected dataset is late, missing or stale.

  27. 27

    Scraper Failure Monitoring & Alerts

    Detecting when a source changes or a collector breaks, and notifying you.

What's included

  • Source review and feasibility check before any build
  • Scraper or pipeline deployed and scheduled
  • Cleaning, normalization and deduplication rules
  • Failure alerting when a source changes or a run breaks
  • Full source code and dataset handover

How it's scoped

Tell us the sources and the fields you need out of them. We check each source for access limits and structure, confirm what is realistically collectable, then build, schedule and monitor the collection. Scrapers break when sites change — so alerting is part of the build, not an extra.

Python & Selenium
Price & market data
ETL pipelines
MongoDB / MySQL
Staffed 24 hours, Monday to Friday

Full-time teams in Chile and India, about nine hours apart. Chile covers your working day; India picks the file up as you sign off, so weekday work does not wait overnight.

Senior-level quality on every assignment

We do not run a lower tier for smaller projects. This work gets the same senior attention as our largest engagements, whether it is a one-page flyer or a client portal.

Send your brief, get it quoted.

First project quoted at a special discount

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