Talend Data Quality Reviews

Enterprise users find Talend Data Quality cost-effective due to its open-source option and integration with Talend Data Integration. Initial setup incurs no costs, making it ideal for evaluation. Pricing varies, with seat licenses costing $10,000-$12,000 annually, and concurrent licenses around $20,000. Users value subscription packages including Data Integration, Data Management, and Data Fabric, accessible based on user numbers. While standard packages are priced reasonably, additional features may require separate purchase.

• "Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."
• "It is cheaper than Informatica. Talend Data Quality costs somewhere between $10,000 to $12,000 per year for a seat license. It would cost around $20,000 per year for a concurrent license. It is the same for the whole big data solution, which comes with Talend DI, Talend DQ, and TDM."
• "It's a subscription-based platform, we renew it every year."

Marketing and advertising companies utilize Talend Data Quality for data ingestion, cleansing, and validation from sources like Google, Bing, and Adobe, storing in systems such as MySQL, S3, and Redshift. In healthcare, they manage PHI/PII compliance and data consistency across applications. Others implement it for data quality checks, reporting, and fixing errors. Master data management is a common use, addressing duplicate records and data consolidation. Interaction with cloud platforms like AWS, Redshift, and Snowflake is also emphasized.

Talend Data Quality customer service receives positive feedback, noted for timely and responsive support. Technical support is generally rated well, although communication challenges sometimes arise. Users praise the knowledge of the support team but acknowledge occasional difficulties in understanding specific business needs. High-tier users experience better service, with agreed service level agreements. Some users find support satisfactory but highlight possible improvements, particularly in expectation management and addressing unforeseen needs.

Users found Talend Data Quality's initial setup generally straightforward with abundant guides. Some experienced challenges, especially without default setups, needing days to resolve. Teams noted easy deployment once familiar with the tool. Memory settings needed adjustments, especially on client systems. The installation simplicity benefited from the Java platform, with additional tweaks documented. Some faced issues after initial success, requiring further troubleshooting. Typically, deployments spanned around four weeks, extending during complex integrations.

Users note Talend Data Quality's scalability varies; some face issues while others find it adaptable with factors like job servers and networking affecting performance. Several instances handle significant projects and increasing users, yet some highlight performance concerns with large data volumes. Java memory adjustments are beneficial, and familiarity with both Talend and Java eases management efforts. Some users do not require scaling, and a few lack enough experience to assess its scalability comprehensively.

Talend Data Quality shows strong stability, although some users report occasional issues with memory leaks, server reboots, or exceptions in the Linux version. Sometimes challenges arise from insufficient memory or machine resources, affecting the studio's performance. Fixing these often involves restarting the application or using a new workspace. While some face isolated script errors, most find it stable for processing large data volumes and rate its stability an eight out of ten.