Omie + BigQuery

Omie is a business management platform designed to meet the needs of small and medium-sized enterprises. BigQuery, on the other hand, is a serverless cloud solution developed by Google, providing robust capabilities for large-scale data storage and analysis.

With Erathos, you can easily set up an Omie to BigQuery integration in just a few minutes. Our platform handles the entire data movement process to your analytical environment and allows this data to be cross-referenced with other sources in your Data Warehouse. This makes the Omie to BigQuery connection seamless and efficient, allowing your time to be focused on what truly adds value — extracting valuable insights and making more data-driven decisions.

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Why Erathos?

Data in your data warehouse in minutes

Data in your data warehouse in minutes

Data in your data warehouse in minutes

Plug and play connectors

More than 50 plug and play connectors to consolidate information from multiple sources, eliminating time-consuming manual processes and establishing a clear path to actionable and reliable insights.

Greater control over pipelines

Transform the way you manage data. Quickly create pipelines by selecting relevant data, configuring the schedule, frequency, and type of update without a line of code.

Edge observability

Stop being caught off guard by data update errors. Set up alerts and notifications in your email, Slack, or Discord to closely monitor the status and execution metrics of the data pipelines.

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Book a demo

No credit card required

No credit card required

What is Erathos?

Gather data from different sources in one place

Erathos is a complete ELT software that extracts data from various sources through instant integrations. With plug & play connectors, you concentrate all your data in a single analytical environment and build a Data Warehouse in minutes.

Our customers

Writing data-driven stories

Writing data-driven stories

"Erathos has revolutionized the way WePayments approaches data management. With its ability to integrate data from multiple SaaS into a single data warehouse, our technical team can now focus more effectively on the company's core business. With Erathos, we’ve been able to implement dashboards that provide insights across all areas of the company. This has not only enriched our organizational culture but also significantly improved our decision-making process."

Matheus Gobato Nunes

CTO & co-founder @WePayments

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"Erathos has revolutionized the way WePayments approaches data management. With its ability to integrate data from multiple SaaS into a single data warehouse, our technical team can now focus more effectively on the company's core business. With Erathos, we’ve been able to implement dashboards that provide insights across all areas of the company. This has not only enriched our organizational culture but also significantly improved our decision-making process."

Matheus Gobato Nunes

CTO & co-founder @WePayments

Read story

"Erathos has revolutionized the way WePayments approaches data management. With its ability to integrate data from multiple SaaS into a single data warehouse, our technical team can now focus more effectively on the company's core business. With Erathos, we’ve been able to implement dashboards that provide insights across all areas of the company. This has not only enriched our organizational culture but also significantly improved our decision-making process."

Matheus Gobato Nunes

CTO & co-founder @WePayments

Read story

Com a confiança de grandes empresas

Com a confiança de grandes empresas

Com a confiança de grandes empresas

Simplified data ingestion

Move your data in minutes

Move your data in minutes

Move your data in minutes

1

Select your data source

Choose your data source between over 50 plug'n'play connectors. You can test each connector for 14 days.

2

Setup your pipeline

Manage your pipeline seemlessly. Select a sync hour, frequency and type at a table/endpoint level.

3

Select your data warehouse

Choose between Amazon S3, BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data

FAQ

Doubts? We have the answers

Doubts? We have the answers

Can Erathos easily integrate data from Omie to BigQuery?

Yes. With Erathos, integrating Omie to BigQuery is simple and fast. You don't need to build custom connectors or deal with technical complexity. The platform continuously moves your data, keeping both environments in sync.

Does Erathos perform any data transformation during the process?

No. Erathos focuses strictly on extraction and loading (EL). This means data is moved from Omie to BigQuery without any changes to its original structure. Any transformation should be handled afterward within your analytical environment.

Can I use Erathos to permanently migrate my data from Omie to BigQuery?

No. Erathos is not a data migration tool. It is designed to create a bridge between Omie and BigQuery, maintaining data in both systems. This allows for continuous operation without decommissioning the source.

How frequently is the data updated between Omie and BigQuery?

The Omie to BigQuery integration via Erathos supports scheduled updates with a minimum interval of 30 minutes. This ensures your analytical environment is consistently refreshed for timely insights.

Do I need to worry about data types in BigQuery?

Currently, all data moved by Erathos to BigQuery is stored as strings. This simplifies the process and avoids type-related errors. If needed, data formatting can be adjusted later within your destination environment.

Can Erathos easily integrate data from Omie to BigQuery?

Yes. With Erathos, integrating Omie to BigQuery is simple and fast. You don't need to build custom connectors or deal with technical complexity. The platform continuously moves your data, keeping both environments in sync.

Does Erathos perform any data transformation during the process?

No. Erathos focuses strictly on extraction and loading (EL). This means data is moved from Omie to BigQuery without any changes to its original structure. Any transformation should be handled afterward within your analytical environment.

Can I use Erathos to permanently migrate my data from Omie to BigQuery?

No. Erathos is not a data migration tool. It is designed to create a bridge between Omie and BigQuery, maintaining data in both systems. This allows for continuous operation without decommissioning the source.

How frequently is the data updated between Omie and BigQuery?

The Omie to BigQuery integration via Erathos supports scheduled updates with a minimum interval of 30 minutes. This ensures your analytical environment is consistently refreshed for timely insights.

Do I need to worry about data types in BigQuery?

Currently, all data moved by Erathos to BigQuery is stored as strings. This simplifies the process and avoids type-related errors. If needed, data formatting can be adjusted later within your destination environment.

Can Erathos easily integrate data from Omie to BigQuery?

Yes. With Erathos, integrating Omie to BigQuery is simple and fast. You don't need to build custom connectors or deal with technical complexity. The platform continuously moves your data, keeping both environments in sync.

Does Erathos perform any data transformation during the process?

No. Erathos focuses strictly on extraction and loading (EL). This means data is moved from Omie to BigQuery without any changes to its original structure. Any transformation should be handled afterward within your analytical environment.

Can I use Erathos to permanently migrate my data from Omie to BigQuery?

No. Erathos is not a data migration tool. It is designed to create a bridge between Omie and BigQuery, maintaining data in both systems. This allows for continuous operation without decommissioning the source.

How frequently is the data updated between Omie and BigQuery?

The Omie to BigQuery integration via Erathos supports scheduled updates with a minimum interval of 30 minutes. This ensures your analytical environment is consistently refreshed for timely insights.

Do I need to worry about data types in BigQuery?

Currently, all data moved by Erathos to BigQuery is stored as strings. This simplifies the process and avoids type-related errors. If needed, data formatting can be adjusted later within your destination environment.

Build, orchestrate, and trust your data

Build, orchestrate, and trust your data

Build, orchestrate, and trust your data

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