They don't have any AI capabilities. Talend DQ is specifically for data quality, which only has data profiling. With Talend DQ, I cannot generate any reports today, so I need an ETL tool. It provides general Excel files, or I have to create some views. If instead of buying a new tool, Talend provides a reporting capability or solution, it would be great. It will reduce the development effort for creating these kinds of reports.

We also manage the infrastructure for Talend. From the licensing perspective, for cloud, they only have seat licenses where one person is tied to one license, but for on-premise, they have concurrent licenses. It would be really awesome if they can provide concurrent licenses for the cloud so that if one person is not there, somebody else can use that license. Currently, it is not possible unless a person deactivates his or her license and moves the same seat license to someone else. We are one of the biggest customers in the central zone of the US for Talend, and this is the feedback that we have provided them again and again, but they come back and say that they aren't able to provide concurrent licenses on the cloud.

In version 7.3, there is a feature for tokenization and de-tokenization of data. This is the feature that we are looking for. It is useful if somebody wants to see what we have masked and how do we demask it. This feature is not there in version 7.1. There are also a few other capabilities on the cloud, but we don't yet have a big footprint in the cloud.

Talend suite might have a missing product, particularly in the commercial master aspect. This would contribute to completing the overall picture, though the focus isn't necessarily on economic considerations. It would be beneficial to have added a greater openness in the tool, allowing for the presentation of data quality results in alternative tools, which would provide increased flexibility in sharing and utilizing data quality outcomes.

• The report generation and using the report in DI job steps could be improved. 
• There are too many functions which could be streamlined. 
• The report generated often has too many pages to go through, if not loaded into a DB.
• There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions.

In terms of improvement, Talend Data Quality needs better dashboarding. Currently, it provides static PDF reports, which are not very dynamic. It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better analysis.

• Displaying columns, which are not part of join, in redundancy analysis.
• You can't join more than two tables for analysis.
• SQL for displaying underlying data in non-match results does not work.

Not enough material is available for beginners.

I would say that some of the support elements need improvement. It is built on open-source technology and they provide platinum support, but they need improvement. We have a large customer base and they need more customized support from them.

I would like to see more advancements with certain big data technology that they have that hasn't been added to the platform. It's something that they could add in the future.

When we upgraded to Version 6.4.1, we tried using a GIT repository instead of a SVN repository. After a few incidents where things disappeared and changes were not saved, we decided to go back to a SVN repository.

There is one place where I would appreciate an upgrade, if it is possible. If the SQL input controls could dynamically determine the schema-based on the SQL alone, it would simplify the steps of having to use a manually created and saved schema for use in the TMap for the Postgres and Redshift components. This would make things even easier. When it does guess the schema it tends to bring back every column from every table or every column from the table specified in the table name in the component. Sometimes, the SQL comes from multiple tables and has some transformations of data. 

I do not know if it would even be possible, but if this could be figured out automatically for the column names and types, that would be amazing.

Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta data.

First, We faced problems with stability of the products. Also some components were clearly not tested well, which meant that there were bugs. Better tools for geo-data are needed. Documentation was poor in the beginning but it got better over time.

I think the memory issues we faced when using the 3GB RAM compared to the 4GB RAM computers caused lot of issues. Probably can improve in that.

I would like to see them add a configuration wizard.

NullPointerExceptions are going to be the death of me and are a big reason for our transition away from Talend. One day, it is fine with a 1000 blank rows, then the next day, it will find one blank cell and it breaks down. When we are dealing with millions of rows of data, this can be super hard to find. 

Heap space issues also plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does. 

Finding assistance with issues can be spotty. With Python, there are literally millions of open source answers which are recent and apply to the version that we are using. 

Inconsistency is a big issue.

The ability to change the code when debugging the JavaScript could be improved.

Toolbox/component integration, performance (optimal memory performance) bench marks / manual across 64bit 32 bit architectures not existent.