IBM Data and AI Ideas Portal for Customers


This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).


Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:


Search existing ideas

Start by searching and reviewing ideas and requests to enhance a product or service. Take a look at ideas others have posted, and add a comment, vote, or subscribe to updates on them if they matter to you. If you can't find what you are looking for,


Post your ideas

Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

  2. Upvote ideas that matter most to you

  3. Get feedback from the IBM team to refine your idea


Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal (https://ideas.ibm.com) - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM.

ideasibm@us.ibm.com - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Employees should enter Ideas at https://ideas.ibm.com


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Status Functionality already exists
Workspace DataStage
Created by Guest
Created on May 28, 2024

RELATED IDEAS

Databricks connector

Adding a Databricks connector to DataStage could bring several benefits. Here are a few reasons why it could be a good idea:

Enhanced Data Integration: A Databricks connector would allow seamless integration between DataStage and Databricks, enabling the transfer of data between the two platforms. This would facilitate data movement and transformation workflows, enhancing overall data integration capabilities.

Scalability and Performance: Databricks is known for its scalability and performance in processing large volumes of data. Integrating DataStage with Databricks would leverage these capabilities, enabling faster and more efficient data processing tasks within DataStage pipelines.

Unified Data Ecosystem: Many organizations use a combination of DataStage for ETL processes and Databricks for advanced analytics and machine learning. Having a connector between the two platforms would create a more unified data ecosystem, allowing seamless data flow from ETL processes to advanced analytics.

Support for Advanced Analytics: Databricks provides powerful tools for advanced analytics, including machine learning and AI capabilities. By integrating DataStage with Databricks, users could leverage these advanced analytics capabilities directly within their ETL processes, enabling more sophisticated data transformations and analysis.

Streamlined Development: A Databricks connector would streamline the development process by eliminating the need for manual data movement between DataStage and Databricks. This would save time and effort for developers, allowing them to focus on building and optimizing data pipelines rather than managing data movement tasks.

Overall, adding a Databricks connector to DataStage would enhance data integration, scalability, and performance, while also enabling support for advanced analytics and creating a more streamlined development process.

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