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 Adaptive Server Enterprise (ASE)
Score 8.0 out of 10
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SAP Adaptive Server Enterprise (ASE) is a transactional relational database, boasting fast, reliable online transaction processing (OLTP). SAP ASE is the company's transactional database within the SAP Business Technology Platform portfolio.
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Pricing
Informatica Cloud Data Quality
SAP Adaptive Server Enterprise (ASE)
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Informatica Cloud Data Quality
SAP Adaptive Server Enterprise (ASE)
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Informatica Cloud Data Quality
SAP Adaptive Server Enterprise (ASE)
Features
Informatica Cloud Data Quality
SAP Adaptive Server Enterprise (ASE)
Data Quality
Comparison of Data Quality features of Product A and Product B
Informatica Cloud Data Quality
8.2
4 Ratings
3% below category average
SAP Adaptive Server Enterprise (ASE)
-
Ratings
Data source connectivity
8.94 Ratings
00 Ratings
Data profiling
8.74 Ratings
00 Ratings
Master data management (MDM) integration
8.24 Ratings
00 Ratings
Data element standardization
7.14 Ratings
00 Ratings
Match and merge
7.94 Ratings
00 Ratings
Address verification
8.44 Ratings
00 Ratings
Relational Databases
Comparison of Relational Databases 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.
We use this for an inbuilt security management system, where it performs well in a scaled setup with a large volume of live data with high availability. Also, the performance is up to the mark for the large statement flow. From a DBA perspective, a lot of parameters need to be fine-tuned for the specific environment needs, which can cause overhead. Expertise is limited, and the learning curve is steep for the SAP ASE.
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.
Well-suited in the security domain, high performance, and low latency of the DBMS. In terms of the DBA perspective, a dedicated monitoring tool (Cockpit) helps a lot in terms of managing the database, which helps in identifying bottlenecks during performance issues. Also, it helps us to send custom alerts related to Database activities.
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.