Likelihood to Recommend Helps to increase productivity, optimize costs, and democratize data across multiple cloud environments with cloud ETL and ELT. Capacity to integrate data sources at scale and with ease. Has cloud data integration capabilities that cover diverse sets of patterns, use cases, and users ensuring we have well-architected and seamless automated data pipelines.
Read full review The same way you design data integration job can be used to design services. It is easy to enhance by custom components and can adapt to all requirements. Talend Data Integration connects to [a] multitude of data sources and streaming service. Very easy interface to design complex applications without spending much time on coding. Easy to learn and master. Talend constantly strives to better itself by adding more features and functionalities.
Read full review Pros The matching algorithms in IDQ are very powerful if you understand the different types that they offer (e.g., Hamming Distance, Jaro, Bigram, etc..). We had to play around with it to see which best suit our own needs of identifying and eliminating duplicate customers. Setting up the whole process (e.g., creating the KeyGenerator Transformation, setting up the matching threshold, etc..) can be somewhat time consuming and a challenge if you don't first standardize your data. The integration with PowerCenter is great if you have both. You can either import your mappings directly to PowerCenter or to an XML file. The only downside is that some of the transformations are unique to IDQ, so you are not really able to edit them once in PowerCenter. The standardizer transformation was key in helping us standardize our customer data (e.g., names, addresses, etc..). It was helpful due to having create a reference table containing the standardized value and the associated unstandardized values. What was great was that if you used Informatica Analyst, a business analyst could login and correct any of the values. Read full review We used Talend to ETLing the data from myriad sources such Oracle Database, Clarify, Salesforce, Sugar CRM, SQL DB, MQ, Stibo Step, FTP, Netezza, and Files. We leverage Talend transformation capabilities for stitching the data , unions and join We successfully created the final unified set that can be used by business Read full review Cons Several partnerships diminishing the value of technologies Unable to get list of objects from Repository (like sources & targets) that don't have any dependency Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this. Read full review Pricing for sure can be the area for improvement. Real time processing is slow as compared to other tools like Abinitio. While developing batches, it crashes a lot. It may be the issue with me, but I wanted to highlight it. Read full review Likelihood to Renew As pointed out earlier, due all the robust features IDQ has, our use f the product is successful and stable. IDQ is being used in multiple sources (from CRM application and in batch mode). As this is an iterative process, we are looking to improve our system efficiency using IDQ.
Read full review Usability Easy to use not only for developers but also business users
Read full review We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.
Read full review Reliability and Availability The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server
Read full review Performance Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.
Read full review Support Rating Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
Read full review Alternatives Considered Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.
Read full review In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, while Talend is more classic. It has both on-prem and cloud approaches, while
Matillion is only cloud-based.
Read full review Scalability Scalability works as expected and it is truly an enterprise system.
Read full review Return on Investment Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production Employee efficiency is increased exponentially due to more automated, customized tool Read full review It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations. 40K+ plots data, covering 1K+ crop varieties. 3K+ Customer & their credit data, 3K+ product inventory & pricing. Read full review ScreenShots