Introducing Prospective's AWS S3 Integration
Prospective's data visualization platform and integration with Amazon S3!
The new S3 adapter enables users to effortlessly connect to data stored in AWS S3 buckets, powering robust data analysis and visualization within Prospective. This integration combines S3's flexibility for hosting a variety of large files from Spark or other workflows with Prospective's high-performance, interactive analytics.
Our focus with this integration is on making data access smooth, highly efficient, and secure, while maintaining the ease of use our users expect from Prospective. Whether you're working with large datasets, partitioned files, or a mix of CSV and Parquet files, the new S3 adapter helps you consolidate all your data in one place for instant visualization and comprehension.
To get a trial license of Prospective, please email hello@prospective.co with the subject "S3 Integration Trial".
Key Features & Functionalities of the S3 Adapter
- Connection Method: Easily connect to your S3 bucket using AWS Signature with Access and Secret keys—(AWS Signature Version 4)
- Supported File Types: Visualize data from CSV, Parquet, Arrow, Excel, and JSON files.
- Multi-file Support: Read multiple files (e.g., partition files) using wildcards ("\*") in file name patterns, such as "census/nc-est2023-\*.csv".
- File Picker Interface: Use our simple object picker dialog box to browse and select files directly from your S3 bucket.
Known Limitations
- Currently, only simple row or column oriented JSON format are supported. Examples:
Row oriented:[ {"a": 12, "b": 13, "c": "hello"}, {"a": 18, "b": 0, "c": ""} ]
Column oriented:{"a": [12, 18], "b": [13, 0], "c": ["hello", ""]}
Step-by-Step Guide on How to Use the S3 Adaptor
- Log into Prospective: Visit https://prospective.co/ and log in using your credentials.
- Access Data Sources: In the top-right corner, click on the SOURCES button, then select S3 from the drop-down list.
- Enter S3 Credentials: Provide your Access ID and Secret Key to authenticate the connection.
- Select Region, Bucket, and Content Type: Choose the appropriate AWS Region and Bucket, then specify the file content type. You can leave the content type set to "auto" to allow Prospective to automatically detect supported file formats like CSV and Parquet.
- Use Wildcards for Multiple Files: If you need to read multiple files with a similar prefix (e.g., all parts of a partitioned dataset), use the wildcard syntax ("\*") in the file name.
- Import and Visualize Data: Prospective will connect to the selected data source and import all rows. From there, use Prospective as you wish 😎
Conclusion
Our new AWS S3 integration is designed to make accessing and visualizing large datasets faster than ever! Whether you're a data scientist, engineer, or executive, Prospective empowers you to turn your raw data into interactive and sharable dashboards.
Ready to get started? Sign up for a trial and experience the power of Prospective with AWS S3 today.
Email: hello@prospective.co with the subject "S3 Integration Trial"
