Hevo changelog hevodata.com

Hevo has extended support for BigQuery Partitioned tables and allows to direct your data to the desired partition table within BigQuery. This can improve your query performance, and control costs by reducing the number of bytes read by a query.

Documentation: Table Partioning in BigQuery

We have added support to extract data from Additional Fields provided by AppsFlyer. This will help you extract and analyze your AppsFlyer Data better.

Here is the list of fields that we have added support for.

We are excited to bring you Hevo's Data Lake as a Service. This is in Private Beta and is open for guided pilots.

Now, you do not have to bring all your raw data to the warehouse. Using our ready-to-scale Data Lake as a service, you can build your Data Lake from scratch using Hevo, model the data, and only push aggregated data to the warehouse. All of this, in a matter of few minutes.

Previously, Hevo used to suggest Decimal data types to be mapped to BYTES datatype in BigQuery. Now, Hevo suggests BigQuery’s numeric type which the right column type to map the Decimal data type.

Rest API source now allows you to have date/datetime query parameters which are printed as epoch timestamps in the URL.

This gives you more flexibility to pull data from sources that only allow epoch timestamp as parameters.

In transformations, you can now avail some handy utilities to help write transformations easily. Addition of these utilities reduces the amount of code you would have to write, making data transformation a breeze for you.

Refer the documentation for complete details: Event, Utils, TimeUtils.

Hevo will now provide detailed notification within the platform on any changes/updates in your account. For errors/failures, you will receive the details on failure reason, time of failure, and more.

You can customize these notifications to receive updates on only the things that matter to you.

Hevo now gives you an option to choose how to parse Nested JSON Fields in events while creating a Pipeline with MongoDB source.

You can choose between the following:

• Flatten JSON fields - The event will be flattened and nested JSON fields will be merged with the top level fields. The names of the flattened fields will carry a period(.) to mark the parent field from which they are coming from.
• Split JSON fields - The event will be split and nested JSON Fields will be ingested as child events to the original event. The child events will carry a property _hevoref_id representing the identifier of the original event.
• Collapse JSON fields - Nested JSON fields will be collapsed and serialized as JSON string.

These options will be extended to other sources as well in the future. Stay tuned!

Hevo now lets you re-order columns while creating tables in destination. This will allow you to have the correct order of columns, primary keys, and other keys.

You can now use Run Now option in the Pipelines and Pipeline Job actions menu to trigger a Pipeline or Pipeline Job on-demand. The Pipeline or the Pipeline Job will be executed once irrespective of the schedule.