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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Progress DataDirect
Score4.5 out of 10
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Progress Software offers DataDirect, a data connectivity solution which helps enterprises integrate data across relational, big data and cloud databases.
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Pricing
Informatica Cloud Data Quality
Progress DataDirect
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Informatica Cloud Data Quality
Progress DataDirect
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Features
Informatica Cloud Data Quality
Progress DataDirect
Data Quality
Comparison of Data Quality features of Informatica Cloud Data Quality and Progress DataDirect
Feature
Informatica Cloud Data Quality
8.2
4 Ratings
4% below category average
Progress DataDirect
-
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
Data Source Connection
Comparison of Data Source Connection features of Informatica Cloud Data Quality and Progress DataDirect
Feature
Informatica Cloud Data Quality
-
Ratings
Progress DataDirect
9.8
2 Ratings
16% above category average
Connect to traditional data sources
00 Ratings
9.52 Ratings
Connecto to Big Data and NoSQL
00 Ratings
10.01 Ratings
Data Transformations
Comparison of Data Transformations features of Informatica Cloud Data Quality and Progress DataDirect
Feature
Informatica Cloud Data Quality
-
Ratings
Progress DataDirect
9.3
2 Ratings
13% above category average
Simple transformations
00 Ratings
9.52 Ratings
Complex transformations
00 Ratings
9.02 Ratings
Data Modeling
Comparison of Data Modeling features of Informatica Cloud Data Quality and Progress DataDirect
Feature
Informatica Cloud Data Quality
-
Ratings
Progress DataDirect
9.7
2 Ratings
20% above category average
Data model creation
00 Ratings
9.52 Ratings
Metadata management
00 Ratings
9.52 Ratings
Business rules and workflow
00 Ratings
9.52 Ratings
Collaboration
00 Ratings
10.01 Ratings
Testing and debugging
00 Ratings
9.52 Ratings
Data Governance
Comparison of Data Governance features of Informatica Cloud Data Quality and Progress DataDirect
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Hybrid Data Pipeline lets users consume or share data in can timely and compliant manner regardless of the application they use or the location of the data. It has defined a stringent set of policies and practices around product development and distribution. Enables customers to consume their data in your application using their BI tool of choice.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info