While our services have a flat fee that covers infrastructure and maintenance, Professional Services refers to custom development work beyond that infrastructure. This includes building new pipelines, pipeline initialization, or developing specialized pipelines for your specific needs. Pipeline initialization is billed separately from the flat fees. These services are scoped on a project-by-project basis and charged at an hourly rate.

Our flat fee covers the entire data infrastructure we own and maintain. This includes data pipelines for extracting and processing your data, cloud storage and computing infrastructure on AWS/GCP, data modeling and testing capabilities, and data warehouse setup and management. We handle all the technical infrastructure between data extraction and your BI tools, ensuring reliable data processing and storage. This includes maintenance, updates, and monitoring of the entire pipeline infrastructure.

A data source is any system or platform that contains data you want to analyze. This includes traditional databases like MySQL or PostgreSQL, cloud services and SaaS platforms such as Salesforce, HubSpot, or Stripe, any kind of API endpoints, file storage systems like SFTP servers or S3 buckets, spreadsheets, and event tracking systems.

We offer flexibility in how you visualize and analyze your data. If you already use business intelligence tools like Tableau, Power BI, Looker, or other platforms, we can seamlessly integrate our data warehouse with your preferred solution. For teams without existing BI tools, we provide access to our sophisticated in-house analytics platform, which offers comprehensive visualization capabilities, custom dashboards, and automated reporting features. This ensures you have powerful data analysis capabilities regardless of your tooling preferences.

While we typically provide and manage the complete data infrastructure, some organizations prefer to use their own existing data infrastructure or dedicated compute resources. This option allows you to leverage our services while maintaining your data within your own systems and infrastructure setup. This can be beneficial for companies with specific compliance requirements or those who have already invested in their own robust data infrastructure.