The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.
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Lob
Score 8.8 out of 10
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Lob in San Francisco provides the building blocks for developers to automate offline correspondences. Enterprise companies use Lob’s suite of APIs to mail fully dynamic and personalized customer communications with print media. Lob also provides insight into deliverability with piece-by-piece tracing and a proprietary Print Delivery Network to streamline production across fully redundant nodes all over the country.
For effective data collaboration, systematic verification of customer information, and address, among others, Informatica Data Quality is a fruitful application to consider. Besides, Informatica Data Quality controls quality through a cleansing process, giving the company a professional outline of candid data profiling and reputable analytics. Finally, Informatica Data Quality allows the simplistic navigation of content, with a dashboard that supports predictability.
Lob has always been able to show us our mailing and projected volume very timely and accurately, and has consistently delivered solutions in the majority of cases. However, due to the complexity and variability of the insurance industry, unique situations occasionally arise that may fall outside their current capacity or operational model.
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.
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.
In my opinion, the admin usability is horrendous. Specifically when looking for specific mailers, the search and pagination UI requires back end loading, it doesn't allow opening in new browser windows, it doesn't remember state when clicking into mailer requiring you to search again. I've started using Claude Code integrated with the API instead of clicking through the Admin UI because, in my experience, it is so hard to use.
IDQ is used by a department at my organisation to ensure and enhance the data quality. The usage was started with address standardization and now it had been brought to altogether a next level of quality check where it fixes duplicates, junk characters, standardize the names, streets, product descriptions. In the past we had issues mainly with duplicate customers and products and this were affecting the sales projection and estimates.
Root keeps Lob because it is already deeply integrated into our systems, and replacing it would require significant engineering effort with limited expected cost savings. As well as the unknowns that come with other options, switching vendors would likely require a significant multi-quarter effort without clear cost savings or efficiency gains.
