Creating and maintaining your web scraping project can be tricky.
We created infrastructure to help you create and maintain quality of data pipelines. You can use it for your personal projects or apply to your growing business needs.
Break down your data aquisition project into smaller tasks,
organazie them into projects. Create and supervise
pipelines with few easy steps.
First, define your data need. You can
either upload XLS, use existing schema,
or use JSON schema to define your data.
You will also specify where to fetch data
and how frequently it should be updated.
Submit solution as Python code and get immediate feedback wether your output is correct. If will be validated against schema you have been submitted previously. It can also
Before running your pipeline on a regular basis, it’s crucial to ensure the data quality is accurate. To maximize effectiveness, combine human peer review with automated quality check tools.
Once you’ve verified the quality of your data pipeline, you can schedule it to run regularly, ensuring that your data collection remains up to date. We will take care of your code run executions.
Manage pipeline dashboards and review progress,
notice any quality issues early. Manage pipeline dashboards and review progress, notice any quality issues early.
Get email alert whenever invalid snapshot of data is procuded or pipeline is not sucessfully completed at all. Qucikly go to link
and fix your solution.
Finaly, download data via web interface (via XLS) or use our APis to access data from your pipelines in JSON and integrate into your daily workflow - wether its product, or business intelligence tools like Power BI.