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Astera 10.4 revolutionizes data management with Google BigQuery and Azure Data Lake connectors, Excel Worksheet Parameterization, and AI-driven mapping precision.
Furthermore, explore advanced API Management capabilities, Cloud Browser in Scheduler, refined AI features in Astea Report Model, and innovations like GraphQL APIs.
Experience a data revolution with Astera 10.4's user-friendly drag-and-drop interface, simplifying complex tasks without the need for coding. Elevate your data journey as the intuitive design puts advanced management capabilities at your fingertips, ensuring a seamless and efficient process.
Unleash the potential of your data management with this intuitive and transformative release.
The Worksheet Parameterization feature empowers users to efficiently extract data from specific worksheets in an Excel file through convenient looping mechanisms. When accessing the configuration parameter screen, the option to define the desired worksheet is displayed.
This selection is made flexible and customizable as the worksheet option can be parametrized using variables or a configuration file. This comprehensive feature enhances data retrieval processes, simplifying and optimizing data handling from multiple worksheets in Excel.
In Astera Data Stack, the AI Automapper utilizes semantic relationships to facilitate field mapping. By analyzing the context and meaning of the fields, it intelligently establishes connections and maps them accordingly.
This advanced approach streamlines the process, enhancing accuracy and efficiency in field mapping tasks.
The grid has been made more aligned by making it easier to sort and filter the columns. Connected to an easy interface and to the expression language, this enhancement is a step closer to making it more streamlined.
MongoDB is a document-oriented database in which one collection holds different documents. The MongoDB Destination object in Astera Data Stack provides functionality to write data onto it. This component provides functionality to control how data should be written in collections.
In Astera Data Stack, users will be able to connect with Google BigQuery as a database source or destination. As a source, both flat and hierarchical data can be read. For destination, flat data can be written to Google BigQuery.
Azure Data Lake Gen 2 is a cloud-based big data storage and analytics solution provided by Microsoft Azure. It offers scalable and cost-effective storage for structured, semi-structured, and unstructured data.
The Azure Data Lake Gen 2 provider will be present within the Cloud Connector object in Astera.
In Astera API Management, the user can now make API requests in any content type by providing the content type along with its serialized content string.
In Astera API Management, the user can now make API requests using the application/x-www-form-urlencoded payload content type.
Define a custom response for your deployed APIs when the flow processing does not give an output. This gives developers flexibility in designing APIs according to the desired standards.
Improvements have been made to the user-friendliness of the Cloud Browser. Cloud Browser’s support has been added to the Scheduler.
After utilizing the AI Feature to generate the layout, we noticed that certain fields were being replicated within the table collection region.
However, through thorough investigation and refining our prompt, we managed to significantly reduce field duplication by around 80% based on our analysis of the enhancements implemented.
The output generated by our AI Feature used to be stored in a system folder, but there has been a modification to this functionality. Now, the cache is stored in a repository table named AICache.
We've now incorporated an option to sort or unsort the layout of the model. This enhancement adds a sorting feature accessible through the context menu in various regions. By clicking the new sort button, users can conveniently arrange the created fields in alphabetical order.
These changes will be immediately reflected in the data preview as well, and this sorting functionality is applicable across all types of regions, ensuring a more organized experience.
We have added an additional document type support for our AI Feature to extract data and create report models from Account Statements.
GraphQL APIs are a query language and runtime for APIs, enabling clients to request the data they need, reducing over-fetching and under-fetching. They offer a more efficient, flexible, and self-documenting approach to data retrieval and manipulation compared to traditional REST APIs.
Astera API Management now supports the use of GraphQL APIs as the input content type for an API. The feature can be seen within the Input Content Type drop-down menu of the API Client object.
Astera now provides the functionality to extract data from PDFs that contain scanned documents using Optical Character Recognition. This option has now made scanned documents available for extraction to users, minimizing the effort of manual data entry from such documents.
Users can select the Resolution for OCR, allowing them to get the best result for their documents.
The Toast Notification feature in Astera Data Stack has seen quite a lot of improvement and enhancement, making it more efficient and seamless.
In Astera Data Stack, the AI mapping approach has been changed. The product is now implementing a Waterfall model for this feature.
In Astera 10.4, many bugs have been addressed user experience has been improved by enabling automatic refresh after actions like adding a catalog item. Other than that, manual refresh is no longer required.
Support for the Report Source object has now been added to the resource catalog.
The Azure SQL Database is a fully managed platform as a service (PaaS) database engine that handles most of the database management functions such as upgrading, patching, backups, and monitoring without user involvement.
In Astera 10.4, the Azure SQL Server authentication is available.
This concludes the Astera 10.4 release notes.
