DATA SOLUTION
Keep Your Data Fresh, Automatically.
Keep datasets updated automatically according to business requirements.
THE CHALLENGE
Getting reliable scheduled data from the web is harder than it looks.
Stale datasets
Manually refreshed data becomes outdated quickly, leading to decisions based on outdated information.
Fragile schedules
Cron jobs and ad-hoc scripts break silently and are hard to monitor across many sources.
Source availability
Sources slow down, block requests, or change structure, breaking automation without warning.
Delivery failures
Even when extraction succeeds, delivery pipelines can fail silently and go unnoticed.
Historical context
Without retained snapshots, trend and elasticity analysis becomes impossible retroactively.
Operational overhead
Managing refresh cadence, monitoring, alerting, and maintenance across dozens of sources becomes a permanent engineering burden.
THE MYDATASCRAPER APPROACH
From fragmented web pages to structured business intelligence.
MyDataScraper builds refresh workflows that run on your schedule, validate each batch, deduplicate records, and deliver updates through your preferred channel — with freshness monitoring, alerting, and maintenance built in so your applications and dashboards always work with reliable, up-to-date data.
What you can build with Real-Time & Scheduled Data.
Hourly updates
Refresh pricing, availability, or monitoring data every hour.
Daily updates
Standard daily refresh for catalogs, listings, and market snapshots.
Weekly updates
Ideal for research datasets and slower-moving markets.
Custom intervals
Define any cadence your business requires, including peak-hour adjustments.
Near real-time workflows
High-frequency refresh where source and use case support it.
Webhook triggers
Push updates to downstream systems when monitored data changes.
Freshness monitoring
Track data freshness and alert when records go stale.
Failure alerts
Notify when a refresh fails or a source blocks access.
Historical snapshots
Retain previous states for trend, elasticity, and audit analysis.
Multi-channel delivery
Combine API, database, file, and warehouse deliveries in one workflow.
Build the dataset around your required fields.
| FIELD | EXAMPLE |
|---|
Available fields depend on the source website and specific use case.
Collect data from the sources your business depends on.
WEB SOURCES
- Websites
- Marketplaces
- Directories
INTERNAL SYSTEMS
- Applications
- Databases
- Data warehouses
ANALYTICS & BI
- Dashboards
- BI platforms
- Reporting tools
DOWNSTREAM WORKFLOWS
- Webhooks
- Automation platforms
- Notification systems
Sources can be evaluated based on your target data and collection requirements. Not every website can be supported.
A data workflow designed around your requirements.
-
01
Define
Identify sources, fields, locations, filters, and update frequency.
-
02
Extract
Collect relevant information from the selected sources.
-
03
Structure
Normalize fields and standardize records.
-
04
Validate
Check records, remove duplicates, and apply quality controls.
-
05
Deliver
Send data through the selected delivery method.
Receive your data the way your systems need it.
How frequently can the data be updated?
One-Time
A single dataset delivered once.
Daily
Refreshed every day.
Weekly
Refreshed every week.
Scheduled
Custom intervals you define.
Near Real-Time*
Where the source and workflow allow.
*Update frequency depends on source availability, technical requirements, and the specific workflow.
What businesses use this data for.
Pricing systems
Keep pricing and revenue systems working with current market data.
Availability monitoring
Track stock, inventory, or booking availability in near real-time.
Listing platforms
Refresh property or travel listings daily for search and discovery.
Market dashboards
Power BI and analytics dashboards with freshly updated data.
Trend analysis
Build historical datasets for elasticity, trend, and forecasting.
Warehouse sync
Feed data warehouses with scheduled bulk refreshes.
Alerting workflows
Trigger downstream actions when monitored data crosses thresholds.
Bulk reporting
Deliver periodic bulk datasets for reporting and analytics teams.
Built for teams across data-intensive industries.
API DELIVERY
Put real-time & scheduled data directly into your application.
Access structured data through an API instead of maintaining extraction infrastructure yourself.
Illustrative example only. Endpoints and fields are defined per project.
GET /api/schedules/products? frequency=hourly window=06:00-22:00
{
"schedule_id": "sched_prod_hourly",
"frequency": "hourly",
"window": "06:00-22:00",
"last_refresh": "2026-10-02T09:00:00+05:30",
"next_run": "2026-10-02T10:00:00+05:30",
"records": 1284,
"status": "on_time",
"delivery": [
"api",
"bulk_feed"
],
"history_retained": true
}
See the data before you build around it.
Review a sample dataset to understand the structure, fields, and level of detail available for your use case.
| DATASET | FREQUENCY | LAST REFRESH | NEXT RUN | STATUS | DELIVERY |
|---|---|---|---|---|---|
| Product pricing | Hourly | 2026-10-02 09:00 | 2026-10-02 10:00 | On time | API + Feed |
| Competitor prices | Hourly | 2026-10-02 09:00 | 2026-10-02 10:00 | On time | API |
| Property listings | Daily | 2026-10-02 06:00 | 2026-10-03 06:00 | On time | Database |
| Travel fares | Every 4 hours | 2026-10-02 08:00 | 2026-10-02 12:00 | On time | API |
| Market research | Weekly | 2026-09-30 03:00 | 2026-10-07 03:00 | On time | Warehouse |
More than extraction.
Data engineering
Design workflows around your actual data requirements.
Structured output
Receive consistent and analysis-ready datasets.
Custom workflows
Choose sources, fields, frequency, and delivery around your use case.
Ongoing data operations
Support recurring workflows as source structures and requirements evolve.
Frequently asked questions.
What update frequencies are supported?
Hourly, daily, weekly, custom intervals, and near real-time workflows where the source and use case support it.
Can I combine different frequencies for the same dataset?
Yes. For example, higher frequency during business hours and lower frequency overnight.
What counts as "near real-time"?
Typically updates every few minutes, subject to source rate limits and workflow design.
How do you handle delivery failures?
Delivery pipelines are monitored and alerts are triggered when a refresh or delivery fails outside expected ranges.
Can I get data pushed to my systems automatically?
Yes. Data can be delivered via API, database sync, cloud storage, webhooks, or scheduled file feeds.
Do you maintain historical snapshots?
Yes, where required. Historical snapshots are commonly used for trend, elasticity, and audit analysis.
Can I trigger a refresh on demand?
Yes. On-demand refreshes can be configured alongside scheduled ones for special cases.
What output formats are available?
JSON, CSV, Excel, database delivery, cloud storage, or a custom integration.
Can you deliver data to a data warehouse?
Yes. Deliveries can be configured for BigQuery, Snowflake, Redshift, or your preferred warehouse.
How do you handle source changes?
Recurring workflows are maintained and adjusted as source structures change so refresh pipelines keep running without engineering work on your side.
Can you combine real-time API access with scheduled bulk feeds?
Yes. Many clients use an API for live queries and a scheduled feed for analytics.
Can you provide a sample workflow?
Yes. Request a sample to review the refresh structure, cadence, and delivery format for your use case.
Build the Real-Time & Scheduled Data workflow your business needs.
Tell us what data you need, which sources matter, how often it should be updated, and how you want to receive it.