A data model consists of 1+ data connector(s), data transformation logic to structure the data and 1+ data destination(s). You can create simple data models with just 1 data connector and 1 data destination, without transforming the data, or more complex models with multiple data connectors, data transformation logic and multiple data destinations.

Datahive360 automatically preserves historical data for connected data sources as time progresses. This means that for data sources where the availability of historical data through the API is limited, Datahive360 enables you to extend the historical reach of your reporting.

Depending on the data source, some data may not be final until several days later (eg. cost and conversion data). Therefore each data connector in Datahive360 has its own lookback window to constantly update data for the time period where data is known to be unstable, ensuring data completeness and overall quality.

Datahive360 takes into account that the data retrieval process could fail due to circumstances beyond our control, like expired credentials or a failed server connection to a data source API. In such an event, our data connectors continuously retry the API requests to let the problem self-heal, ensuring data completeness and overall quality at all times. Platform

Datahive360 helps users manage their API usage quotas automatically. Datahive360 checks the available limits and makes sure its data extraction calls won’t exceed those limits while still being able to collect all the data.

This feature provides a seamless experience for users, as it guarantees optimal data collection without user interference. It helps prevent unexpected API usage spikes and avoiding or minimizing any additional charges or penalties.

While Datahive360 offers fully automatic data unification, you’re fully in control. Using a visual ETL workflow you can always manually configure field mapping/binding for every data source in your data model. Start with one of our pre-build data model templates and customize it to your needs, or build one from scratch.

Datahive360 recognizes metrics and dimensions across different data sources and understands how to handle field mapping/binding automatically. Your data is therefore automatically unified and harmonized using fully customizable data model templates.

Access your data at the most detailed level or ‘as raw as provided’ through the API. Even if you use Datahive360’ automatic data unification, data will also be stored on a granular level.

A generic 3rd-party data connector that enables a zero to low-code creation of custom data connectors to platforms for which Datahive360 does not have a plug & play connector yet. Any data source using common verification techniques and data-interchange formats like JSON can be easily added with little to no technical knowledge.

Datahive360 offers plug & play connectors for the most popular advertising, analytics and CRM platforms. See the list of supported data connectors for details.

Templates in Datahive360 enable you to create even the most complex data models with ease. There are a lot of templates available which you can customize to your needs. You can even create templates yourself for deployment across multiple accounts.

Datahive360 supports the use of webhooks in data models. A webhook (also called a web callback or HTTP push API) is a way for an app to provide other applications with real-time information. You can use webhooks to send notifications or deliver data from Datahive360 to other applications as it happens, meaning you get data instantly.