I would rate Talend Data Quality a nine out of ten.

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The key to success lies in the adoption of the solution within the customer's processes and services. My recommendation is to initiate the implementation by focusing on critical data. By starting with essential data sets, you can swiftly demonstrate tangible results to the business. This approach is strategic because, often, the technical aspects of the technology are not easily comprehensible to the business stakeholders. Begin with a small yet high-value segment to enhance data quality, and then gradually extend the implementation to cover the entire organization. This phased approach ensures a smoother transition and a more significant impact on overall business processes. Overall, I would rate it eight out of ten.

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My advice to new users is that if you are looking to identify data issues, I would recommend Talend Data Quality as a cost-effective and efficient choice. However, if you also want to enforce rules and handle discrepancies, Talend Data Quality may not be enough, and you should consider Talend's integration solutions for a more comprehensive approach. Overall, I would rate the solution an eight out of ten.

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The Studio is easy to understand. The analysis and reports are easy to build as well. We have been using it for the past four to six months now. We do not have many analyses created though. Since our Portal is not working, we are not using it to its full potential, which I want us to use. Therefore, this product has room for improvement. 

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It's a great technology.

Be careful of the add ons and there are different packages. Most customers are fine with starting off with Data Management, but there are add ons. I would suggest sharing the requirements or the scope with Talend so that they have an understanding of the work features that are required to grow with the right brand of data fabric for data management. 

It's one of the leading platforms. It has customers who are looking for a good and cost-effective data integration platform, that can connect with multiple technologies. 

It has data integration and data management capabilities, which is why many customers use Talend, but there are some elements with the support that they need to look at.

I would rate this solution an eight out of ten.

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Keep your jobs small and simple, split large jobs into multiple smaller jobs. One of the major pitfalls is creating one huge job which does everything. This is detrimental for the performance of the job. It also makes it harder to read and understand the job, let alone debug the job.

Always use metadata and contexts groups. Deploying will be a lot easier.

Use the documentation possibilities in your jobs. Name the component, data flow, and sub jobs. This will increase the readability of the jobs.

I would give it an eight out of 10. In the last four years I have seen the product grow and improve but there is still more room for improvement.

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I have not run into anything we could not use Talend to find a solution for.

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Put in a server with a lot of memory and if it’s a hard process then put in a dedicated server. View full review »

I would definitely recommend others to implement this product as it is really helpful, easy to learn, user friendly, provides lot of enhanced features, etc.

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Great product, surely give it a try.

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I rate Talend Data Quality a nine out of ten.

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It is a good tool; include it in your planning.

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Account for Java developers/ custom development efforts apart from DQ functional/technical expertise, to use Talen DQ product to the fullest. View full review »

Platform/Technology specific decisions need to be made upfront before considering this solution.

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