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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SAP Data Quality Management
Score 8.9 out of 10
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SAP Business Objects Data Quality Management embeds data quality functionality into SAP applications.
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 …
IDQ was a best fit for our data quality management, but we didn’t have a lot of Informatica services to integrate with it hence we implemented SDQ instead.
Features
Informatica Cloud Data Quality
SAP Data Quality Management
Data Quality
Comparison of Data Quality features of Product A and Product B
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.
When reporting, we use accurate data with no duplications since they are addressed by SAP DQM, we get the right target audience by analyzing marketing data, and also helps us to understand the current situation of our firm by comparing metrics.
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.
Has a suite of applications and components that we can integrate with Informatica Power center to deliver enterprise-strength data quality capabilities in a wide range of scenarios. Provides comprehensive and modular support for all data and all use cases whether in small or complex projects. Streamlined data discovery with a broad and deep lineup of enterprises.
The client was on a SAP platform for most of their applications and also is planning to implement SAP Hana very soon. This tool was fitting good for the requirement of the client to manage the quality of the data and hence adapt it in the system. Also, it can go well with the BO reporting.