After several months working on our back end to make our product more stable and user friendly the focus in 2022 will go into launching new features. We will not just launch any feature, features will be dictated by our current customers.
That is why we are excited to announce our new batch of features:
- Azure SQL
- Code Operator
- Delete Integrations and Models at project level
1. Azure SQL:
With this feature clients will be able to send the output of their data pipelines directly into Azure SQL. This way clients will be able to easily keep their data up to date in their DB and not only that, will be able to control it by having a “full circle” process from data ingestion to production.
2. Code Operator:
This is one of our biggest bets this year. So far Datagran has been a platform aimed toward operationalizing models. With this new feature which is the first step of our plan (see features to be released for more information) we are also moving towards Code. With the Code Operator users will be able to upload their python code to process data.
For a full explanation on how this Operator work please read our documentation here https://proud-botany-7dd.notion.site/Code-Operator-3c5978b7435040ad9609eb93ba639992
3. Delete Integrations and Models at project level:
One of the big advantages in Datagran is that users can create projects and assign specific models, people and integrations to them. Starting today users will be able to delete Integrations and models at project level in addition to our current support of deleting people.
Features to be released in the next 3 months
- New Sign Up and Sign in:
A more user friendly interface optimized for mobile with Google Sign in and Sign Up.
- Shopify Integration:
We will be re launching one of our most requested integrations.
- Real Time logs:
Users will be able to see real time logs every time they run a pipeline or an operator. Now debugging models will be a breeze.
- Rest API integration:
Users will be able to bring data from any API.
- Code IDE:
This is the continuation of the Code Operator. In this step users will have the flexibility to code inside Datagran in a Jupiter Notebook kind of environment that will support Python, R and more.
- TensorFlow support for Custom Code Operator:
Will be the addition of our second library besides Scikit Learn.
Let us know if you would like another feature that’s not listed in here. Would love to hear from you.