We extract server configurations, networking hardware, software catalogues, and vendor specifications from Computacenter. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Servers & Storage objects from computacenter.com. All fields typed and schema-versioned.
"sku": "DL380-G10-8SFF", "manufacturer": "HPE", "product_name": "ProLiant DL380 Gen10 Server", "form_factor": "2U Rack", "processor_type": "Intel Xeon Silver 4208", "ram_capacity": "32GB RDIMM", "storage_capacity": "None standard", "power_supply": "500W Platinum"
| # | sku | manufacturer | product_name | category | form_factor | processor_type |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Networking Gear objects from computacenter.com. All fields typed and schema-versioned.
"sku": "C9200L-48P-4G-E", "brand": "Cisco", "model_number": "Catalyst 9200L", "device_type": "Switch", "port_count": 48, "poe_budget": "740W", "management_type": "Managed", "availability_status": "In Stock"
| # | sku | brand | model_number | device_type | port_count | port_speed |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Workplace Devices objects from computacenter.com. All fields typed and schema-versioned.
"sku": "20XW004JUK", "manufacturer": "Lenovo", "product_family": "ThinkPad X1 Carbon Gen 9", "screen_size": "14.0 inch", "cpu_model": "Core i7-1165G7", "memory": "16GB LPDDR4x", "storage_ssd": "512GB NVMe", "os_version": "Windows 10 Pro"
| # | sku | manufacturer | product_family | screen_size | cpu_model | memory |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Software & Licensing objects from computacenter.com. All fields typed and schema-versioned.
"sku": "MS-O365-E3-ANN", "vendor": "Microsoft", "software_name": "Office 365 Enterprise E3", "license_type": "Subscription", "user_count": 1, "subscription_term": "12 Months", "delivery_method": "Electronic Download", "support_tier": "Standard"
| # | sku | vendor | software_name | license_type | user_count | subscription_term |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Accessories & Peripherals objects from computacenter.com. All fields typed and schema-versioned.
"sku": "910-005694", "brand": "Logitech", "category": "Peripherals", "sub_category": "Mice", "product_name": "MX Master 3 Wireless Mouse", "connection_type": "Bluetooth / USB Receiver", "color": "Graphite", "warranty_period": "1 Year"
| # | sku | brand | category | sub_category | product_name | connection_type |
|---|---|---|---|---|---|---|
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Our Computacenter scraper navigates complex B2B categories, extracts deeply nested hardware specifications, and structures vendor catalogues into queryable datasets.
Extract granular technical details including form factors, processor models, RAM configurations, and power supply ratings for servers and workstations.
Capture port counts, PoE budgets, management types, and stacking capabilities across Cisco, Aruba, and Juniper catalogues.
Monitor public inventory statuses and lead times for critical infrastructure components to optimise procurement planning.
Normalise SKUs and product families across major enterprise vendors like Dell, HP, Lenovo, and Apple.
Extract direct URLs to PDF datasheets, compliance documents, and vendor installation manuals linked on product pages.
Capture subscription terms, license types, user tiers, and platform compatibility for enterprise software products.
Reconstruct the full Computacenter category tree to maintain hierarchical relationships between parent categories and sub-categories.
Extract lists of compatible accessories, cables, and warranty extensions associated with primary hardware SKUs.
Track new SKU additions, deprecated hardware, and specification updates across the catalogue with hash-based diffing.
Brief in. Clean data out.
Provide target categories, vendor lists, or specific hardware families. We map the extraction schema to your requirements.
We configure Scrapy crawlers and Playwright sessions to navigate the B2B portal, handle pagination, and parse technical tables.
Schema validation, null-rate checks on critical specifications, and data type normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on your defined schedule.
Enterprise IT distributors use complex category structures and dynamic loading. Here is how we ensure reliable data extraction.
Many hardware specifications load dynamically via JavaScript after the initial page request. We use Playwright to execute these scripts, ensuring technical tables are fully populated before extraction.
B2B portals have deeply nested category trees. Our crawlers systematically traverse these hierarchies, maintaining the parent-child relationships so you know exactly where a SKU sits in the catalogue.
Different vendors format specifications inconsistently. We apply regex and custom parsers to normalise attributes like RAM capacity and processor speed into standard numeric formats.
To prevent IP bans from aggressive crawling, we route requests through residential proxies and enforce strict concurrency limits, mimicking legitimate business user behaviour.
Re-scraping the entire IT catalogue daily is inefficient. We maintain a state file of known SKUs and only emit records when new products are added or specifications change.
Enterprise procurement teams monitor available SKUs and hardware lifecycles to optimise their purchasing strategies.
Hardware vendors track how their products and compatible accessories are positioned and categorised by major distributors.
ITAM platforms enrich their internal databases with accurate manufacturer specifications and end-of-life indicators.
Rival IT service providers monitor Computacenter's public catalogue to identify gaps in their own hardware offerings.
Analyst firms track the introduction of new server generations and networking standards across distributor catalogues.
Engineers extract detailed technical specifications to design compatible infrastructure architectures for clients.
"Enterprise IT catalogues hold the ground truth for hardware lifecycles and specifications. Extracting this data transforms static PDFs into a queryable infrastructure database."
Manually updating IT asset databases or relying on fragmented vendor feeds leads to blind spots. DataFlirt automates the extraction of complex hardware specifications, normalising disparate vendor formats into a single, structured schema. We handle the crawling infrastructure so your team can focus on procurement analytics and system design.
Everything supported by our computacenter.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy orchestrates the broad crawl across category trees, while Playwright handles the heavy JavaScript rendering required for detailed product specification pages.
We route requests through region-specific residential proxies to avoid rate limits and capture accurate, localised catalogue data.
Pipelines are scheduled via Apache Airflow and executed on Kubernetes clusters, providing scalable compute for large catalogue extractions.
Data delivered to where your team already works — no new tooling required.
About computacenter.com scraping, legality, and pipeline operations.
Ask us directly →We extract publicly visible MSRP or baseline prices if available on the public catalogue. However, contract-specific B2B pricing requires customer authentication, which falls outside our standard managed service scope.
We extract the base SKUs and available component options listed on the product pages. Fully custom configurations generated via interactive UI flows are typically captured as individual component SKUs rather than pre-built assemblies.
Yes. We apply custom parsing logic to normalise common attributes. For example, '16 GB', '16GB', and '16384 MB' RAM capacities are converted into a standard numeric format in the final dataset.
For large IT distributors, we typically run weekly or bi-weekly full catalogue sweeps. Delta runs to check for new SKUs in specific high-priority categories can be scheduled daily.
We extract the direct URLs to the PDF datasheets and vendor manuals. If required, we can configure a secondary pipeline to download and store the actual PDF files in your S3 bucket.
Scraping publicly accessible product information, specifications, and taxonomy data is generally permissible. We target unauthenticated, public-facing pages and adhere to standard rate limits to avoid disrupting the target servers. Clients should review their own compliance requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually updating specifications. We build and maintain the pipelines to deliver structured IT catalogue data directly to your systems. Contact our engineering team to define your schema.
