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Informatica Intelligent Data Management Cloud (IDMC) vs erwin Data Catalog by Quest comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

erwin Data Catalog by Quest
Ranking in Metadata Management
11th
Average Rating
7.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Informatica Intelligent Dat...
Ranking in Metadata Management
1st
Average Rating
8.0
Number of Reviews
181
Ranking in other categories
Data Integration (3rd), Data Quality (1st), Business Process Management (BPM) (7th), Business-to-Business Middleware (3rd), API Management (7th), Cloud Data Integration (3rd), Data Governance (2nd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Test Data Management Services (4th), Product Information Management (PIM) (1st), Data Observability (2nd)
 

Featured Reviews

Andres-Martinez - PeerSpot reviewer
Mar 21, 2022
Helps with metadata management, saves time, and allows us to do impact analysis on any changes
There are always ways to improve things. For example, we can use AI to be able to find out something. When we are typing something, if we don't know the exact term, Artificial Intelligence would be useful to find terms that are phonetically or syntactically similar. Instead of having to type in the exact name, they can provide those in the list. So, they can provide AI support for the search because when you have thousands and thousands of terms, it is hard to remember all the names. There were some issues when drawing the data models. If you have more than 500 or 600 tables, it takes a long time to display those in the right position on the screen. That can also be improved. They need some caching and some parallel pipelines working on the backend in order to divide it into sections.
Raj Sethupathi - PeerSpot reviewer
Jun 13, 2024
Offers profiling and address standardization but can be complicated
Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process. Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash. Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The data catalog feature is pretty good."
"When you combine it with data lineage, every time you need to make a change, it allows you to do impact analysis on any changes and then connect to the end-users or data stewards so that they can be aware that a change is coming. That's one of the main benefits we use it for."
"Informatica MDM's most valuable feature is the interconnection between multiple Master Data domains."
"Some of Axon's valuable features include creating your business glossaries, importing DQ rules, and creating change management."
"I am impressed by the solution's interface."
"The interface is really good."
"Data integration is the most valuable feature. The ability to connect to any of the sources and enterprise applications makes our lives easier."
"The capability of the tool to scan and capture the metadata from a variety of sources is one of the capabilities that I find most useful. The central repository into which it is going to put that captured metadata is the best."
"REST API: Excellent for scripting control and reporting mechanisms"
"The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data."
 

Cons

"There is room for improvement with respect to the connector and how to connect to the structured and unstructured database."
"There are always ways to improve things. For example, we can use AI to be able to find out something. When we are typing something, if we don't know the exact term, Artificial Intelligence would be useful to find terms that are phonetically or syntactically similar. Instead of having to type in the exact name, they can provide those in the list. So, they can provide AI support for the search because when you have thousands and thousands of terms, it is hard to remember all the names."
"The model is somewhat flexible. There are certain aspects of the model that are not as flexible as we would like. It doesn't do certain things to a great level of depth. So, in situations where we want to drill in to do something specific, we have to essentially copy that data into our own structures in order to add that additional layer of flexibility."
"The data discovery isn't that good yet for Salesforce. We have another tool that we use for this. It may be a problem because Salesforce on the cloud."
"We cannot sell the product directly with an additional layer."
"There could be a lot more application integration."
"There is room for improvement at the highest level in terms of useability and connectors for various types of new applications. The row processing performance could be better because you experience some latency dealing with high volumes of data. Most organizations will be dealing with multiple cloud applications, so you could see performance issues moving from one system to another."
"Once the data is masked, we won't be able to reverse it back to its original value."
"There are also some technical issues sometimes with integrations because clients have a lot of different types of data sources."
"Informatica MDM's UI is not intuitive enough."
 

Pricing and Cost Advice

"I am not very familiar with its pricing. I know it is not cheap, but it is also not super expensive. It depends on the company size. For a company making $1 million, it is very expensive. For a company making 10 million and above, it might be okay."
"Erwin Data Catalog is very expensive."
"It's offers value for money. They're more competitive with respect to pricing and offerings."
"We got a 50% discount."
"Informatica Axon is expensive."
"My understanding is that Informatica is quite expensive compare to other tools that are available in the market."
"Informatica MDM's price could be lower."
"It's an expensive solution."
"The price is high, but the competitors are even higher, like Collibra."
"I rate the product's pricing a five on a scale of one to ten, where one is cheap and ten is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Government
13%
Computer Software Company
11%
Manufacturing Company
9%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
10%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

Which ETL tool would you recommend to populate data from OLTP to OLAP?
There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...
What is your experience regarding pricing and costs for erwin Data Catalog?
Erwin Data Catalog is very expensive. I would rate it a two out of five for affordability.
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
Which Informatica product would you choose - PowerCenter or Cloud Data Integration?
Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...
What are the biggest benefits of using Informatica Cloud Data Integration?
When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...
 

Also Known As

No data available
ActiveVOS, Active Endpoints, BPM, Address Verification, Persistent Data Masking, Cloud Test Data Management, PIM, , Enterprise Data Catalog, Data Integration Hub, Cloud Data Integration, Data Quality, Cloud API and App Integration
 

Overview

 

Sample Customers

Balfour Beatty Construction, Banco de México, BFSI Canada, CenturyLink, Daktronics
The Travel Company, Carbonite
Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. erwin Data Catalog by Quest and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.