There are a couple of valuable features. One is that it is very quick on the profiling. So, you get a very fast snapshot of the type of data that you're looking at from the profiling perspective. It can highlight anomalies in the data.

The other valuable feature of the Data Quality tool is the flexibility of using their Analyst tool to create a mapping specification, which allows you to join multiple sources of information. You can then create rules within that data set. You can apply aggregations and all other types of functions, and then you can feed that into the profiling tool. From the profiling tool, you can then create your scorecards. It can be two-step where you're using that mapping engine to integrate multiple sources. If you don't have a need for that, you can do a lot more sophisticated mappings inside their Developer tool, and then maybe do an analyst type of mapping engine. So, you can do straightforward data quality within the Analyst tool, or you can do more sophisticated data quality within the Developer tool, at least as far as the rules are concerned.

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In my experience, I've specifically worked with a feature called ARS Doctor, which is part of IDQ (Informatica Data Quality). So, in my earlier project, the core functionality of ARS Doctor revolved around address information sourced from the USPS postal service. It does validate the data. This is crucial because customer addresses often contain diverse writing errors. Given the presence of multiple applications, addresses can be inputted or tagged across various systems or enter their address data differently, yet it needs to conform to a standardized format. 

Therefore, each address, even if inputted from distinct systems, undergoes validation to match a single, customizable format. We also have customized settings for these validations.

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I cannot just go into details of the product's features randomly because if you look at a very wide range of overall requirements, be it Informatica or Talend or more data lake solutions like Snowflake. My company goes through an entire range of areas, making it difficult for me to just speak about the features.

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The evaluation service is a valuable feature of this product. 

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The profiling feature in Informatica Data Quality is incredibly effective for data governance. It helps identify data types and potential duplicates, streamlining the detection process. It also suggests matches with predefined fields in our catalog.

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We are satisfied with the entire solution in its current state and eagerly anticipate its transition to cloud technology.

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The most valuable features are data quality, data integrate transformations, match-merge, and a few MDM solutions we build into data quality transformation. 

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It's probably one of the leading lights in ETL. They have really good built-in functionalities, or algorithms, that you can use to transform or process data and validate and standardize.

The solution is stable.

It's not too had to set up the cloud version. 

Support is helpful and responsive. 

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We have implemented both data profiling and data quality transformations for data validation. These are the two major components we rely on, with data profiling helping us understand the data's characteristics, and data quality transformations ensuring data validation.

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The features I find most valuable are the mappings and rules. I am also impressed by the solution's interface. I really like this solution, as it works very well.

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The most valuable feature of this solution is data profiling. We are able to set rules, establish a data quality management platform, and monitor the quality. These features are excellent.

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Seeing the data in the mapping itself is really nice. We don't want to extract the data and just see the flat file. With Data Quality, we can see the data very easily.

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It is very useful for testing purposes and designing mappings for small projects. If you go for IDQ in the mapping itself, you can see the data. You can then correct it, and test it so easily. 

It is working fine. It is also stable, scalable, and easy to deploy.

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Data cleansing and address validation are the most valuable features. Also the web services which can be called on the fly. Data Duplication plays a very important role. View full review »

In terms of Data Quality, the feature most valuable to me is that the solution is applicable for both technical and business users. I like that instead of using on-premises processing power, you can now use your on-cloud platform processing power to process the data and get a faster turnaround time. From a product perspective, everything is well done. 

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The user interface is flexible and the visibility of the data flow is amazing. You can see your data throughout the flow and then you can determine where issues are before fixing them.

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IDQ integration with Power Centre Designer Repository. On the fly you can move your IDQ artefacts to Power Centre Designer. Later you can use them in a workflow and for scheduling etc. View full review »