Informatica Cloud Data Quality Reviews and Ratings

Rating: 6.7 out of 10

Score

6.7 out of 10

Community insights

TrustRadius Insights for Informatica Cloud Data Quality are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Business Problems Solved

Users of Informatica Data Quality, or IDQ, have found the software to be highly effective in addressing various data quality challenges. One key use case is the validation of customer and vendor addresses, ensuring that there are no duplicates and verifying consistency in product descriptions. With simple and logical interfaces, IDQ eliminates the need for complex coding, making it accessible even to nontechnical citizen integrators. This democratization of integrations enables self-service capabilities and empowers users to easily scale up or down to accommodate different workloads without impacting performance.

Another important use case is the tool's support for data validation and cleansing processes. From address verification to content filtering, IDQ offers reliable data quality powered by AI. This allows users to identify and resolve quality issues that can potentially impact business initiatives. The software caters to both business users and developers, providing customization options and seamless integration with Informatica Power Center. Users can gain insights into their data by performing data profiling within the tool. This helps them make informed decisions before executing data quality operations.

IDQ has been extensively used across organizations for contact and address validation, enriching data to drive more effective campaigns. It has proven instrumental in resolving issues related to duplicate customers and products, resulting in improved sales projections and estimates. Users have relied on IDQ to address data inconsistencies, foreign character problems, as well as formatting and formula issues. The software also facilitates standardization of customer addresses, identification of duplicate records, and optimization of data for reporting tools.

Furthermore, IDQ seamlessly integrates with various applications such as Salesforce and SAP. This enables smooth handling of large volumes of records. Its capabilities extend beyond data validation; users leverage IDQ to update customer data with accurate details while identifying duplicate customers. Moreover, it serves as a comprehensive solution for monitoring overall data quality organization-wide, ensuring compliance with data quality standards. By automating technical and business data quality checks across multiple sources, users gain enhanced trust in their data and make more informed, data-driven business decisions.

Reviews

19 Reviews

Better data virtualization with Informatica Daas

Rating: 9 out of 10

Incentivized

October 31, 2022

Use Cases and Deployment Scope

It has great function that will aid using hybrid cloud for data storage possible. Customer support is very well. Data virtualization has made us achieved three major things one reduced expense, reduced risk as well as an improved revenue in total and we have a single access point to monitor the data

Pros

Deliver excellent data virtualization
Reducing expense, risk and increase revenue in total
Single access point to monitor the data

Cons

The product performance is satisfactory in overall

Likelihood to Recommend

It helps us gain quick access to reliable information.It also makes it possible to integrate data from multiple disparage sources

Nagaraj C

Senior Software Engineer in Corporate at KPMG (10,001+ employees)

Vetted Review

1 year of experience

Informatica IDQ leads the way with Data Quality automation

Rating: 9 out of 10

Incentivized

January 28, 2022

Use Cases and Deployment Scope

Automation of technical and business data quality checks on data from over 10 different data sources across various sectors. Access to end-users on the data profiles makes the company proactive in resolving data quality issues which in turn improves the trust in data. Eventually promotes business decisions backed by data.

Pros

Data quality profile
Automation of data quality check
Exception management
Customizable template to capture metadata

Cons

The cloud offering does not have all the features of on-prem version
The DQ report has limit of only a few sample records it shows, it could show more
Ability to delete an older version of metadata from the business glossary

Likelihood to Recommend

It can handle large volumes and a large variety of data. Also, can handle a large number of enterprise users well.

Verified User

Manager in Information Technology (5001-10,000 employees)

Vetted Review

4 years of experience

Swift, Manageable, and Progressive App for Database Enhancement.

Rating: 10 out of 10

Incentivized

December 25, 2021

Use Cases and Deployment Scope

Informatica Data Quality is a solution that pushes companies to take a vibrant step in managing data, enhancing and reinforcing security, and activating all the analytical demands in the business. Further, Informatica Data Quality focuses on data collaboration and standardization, a form that improves the quality and reliability of the database system. Finally, the whole validation and cleansing process is effectively supported by Informatica Data Quality, from address verification to content filtering.

Pros

Perfect data collaboration and detailed standardization. The two procedures support universal acceptability.
Further, the concerned address control and validation increase the accuracy, effectiveness, and reliability of the database.
Finally, Informatica Data Quality has an outstanding cleanser, very rapid, robust, and speedy.

Cons

Data reviewing is not fully encompassed by Informatica Data Quality, which would validate the database.
Besides, third party applications face challenges, due to poor integration support.
Nonetheless, there are proficient, reliable, and contained safety and analytical measures.

Likelihood to Recommend

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.

Angel Caroline

Information Technology Consultant in Information Technology at FCCI Insurance Group (1001-5000 employees)

Vetted Review

3 years of experience

View profile

Informatica Data Quality review

Rating: 9 out of 10

Incentivized

April 12, 2019

Use Cases and Deployment Scope

Informatica Data Quality is a tool that supports business users (non-technical) and developers(technical) in an equal way. It can be enhanced through the customization of rules and policies, and supports seamless integration with Informatica Power Center, with the help of Informatica Data Quality Mapplets. These mapplets can be imported to Informatica Power Center, and can be used within the Data Integration Process.

Data profiling can also be made within the tool, and profiling results give you insight into the data that you are about to use to perform a data quality operation.

However, the more data you profile, the more memory and CPU it needs.

Pros

It performs quality Data Profiling operations.
A web-based data quality check (without the need for any client tool installation).
Seamless integration with other Informatica products.
Ease of use (2 days of training for profiling, 4 days for intermediate development, and 4 days for advanced development skills).

Cons

A hardware monster.
Needs easier security.
Could provide easier administration.
Needs easier installation steps.

Likelihood to Recommend

We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways.

At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.

Gurcan Orhan

Data Quality Management Software Development Manager at Yapı Kredi (10,001+ employees)

Vetted Review

1 year of experience

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Best Product!

Rating: 10 out of 10

January 25, 2015

Use Cases and Deployment Scope

I used Informatica in my previous company for a Finacial Service provider for Data extraction from flat files. Data from various transfer agents (TA) was gathered using Informatica and loaded into Database. I can handles millions of records at one time.

Pros

Informatica provides high-quality data regardless of size, data format, platform, or technology
Address parsing, formatting, and standardization

Cons

It is perfect!

Likelihood to Recommend

Informatica can be used in highly scalable, multiprocessing applications and works very well millions of transactions.

Verified User

Engineer in Information Technology (1001-5000 employees)

Vetted Review

4 years of experience

Informatica Data Quality

Rating: 9 out of 10

April 11, 2014

Use Cases and Deployment Scope

Informatica is used to integrate to various applications like Salesforce, SAP etc. with Oracle and SQL databases. It's used by various departments across the Americas. It helps to optimize the data for various reporting tools.

Pros

Fact & multi-dimensional loading
Tracking Changes in slowly changing dimensions
Integration of data from SAP and Salesforce is better with this ETL tool compared to other tools in the market
Modularity

Cons

Several partnerships diminishing the value of technologies
Unable to get list of objects from Repository (like sources & targets) that don't have any dependency
Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this.

Likelihood to Recommend

Informatica Data Quality provides all projects and initiatives with clean, high-quality data regardless of size, data format, platform, or technology. Less appropriate in scheduling IDQ jobs where needs to rely on third party tool. Key significance in selection process is about the efficiency of usage of tool in long term with reasonable over-head cost.

Verified User

Professional in Information Technology (10,001+ employees)

Vetted Review

1 year of experience

IDQ-Quality enhancer

Rating: 4 out of 10

March 25, 2014

Use Cases and Deployment Scope

We found many data inconsistencies, foreign character problems and issues with simple formats and formulas. Special characters were also one of the many bugs we failed to address in the beginning. Now that we start all the projects with IDQ and only after its help in analysis and fixing the bad data, it helped us with quite a few production tickets. It also helped us with best end user experience.

Pros

Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
Character Set Mapping
Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports

Cons

I think its high time Informatica integrated all tools like PowerCenter, IDQ, IDE , powerexhange into one which will simplify development and maintenance

Likelihood to Recommend

I did not spend any time researching the tool for improvements, but the interface with PowerCenter will make me more interactive and connected to the developers.

Verified User

Professional in Engineering (51-200 employees)

Vetted Review

8 years of experience

IDQ cheap and popular!

Rating: 7 out of 10

March 25, 2014

Use Cases and Deployment Scope

IDQ is used to update the customer data with correct address, name, phone numbers etc. It's used in the Digital IT department at my current organisation. It identifies the duplicate customers and maintains the up to date details of a customer.

Pros

Address Doctor: Automatically suggests and corrects the customer address based on the globals address database. Thus ensuring the correct physical address of the customer
IDQ can be merged with Powercenter very fast and adequately

Cons

IDQ needs some more integration with other ETL tools and databases like Ab nitio, Cognos and Oracle

Likelihood to Recommend

It is well suited where customers are so versatile globally and we have challenges to maintain data from across the world

Verified User

Administrator in Information Technology (1-10 employees)

Vetted Review

8 years of experience

IDQ-Good Tool

Rating: 9 out of 10

March 10, 2014

Use Cases and Deployment Scope

IDQ is used for data cleansing and address validation. Passing Invalid Addresses and getting output as valid address and using these address to send mail to employees. Data cleansing rules while loading data from source to warehouse.

Pros

Address Validator Transformation - makes things so easy.
The algorithm for address validation to would take years to write.
Address doctor standalone application is powerful and can use any ui for performance improvements.
Geocoding of Address doctor is so useful.

Cons

It would be great if it could merge with PC Designer.
This tool will be used in the front end systems -where addresses can be visible to the users.
If address doctor improve like google api for lat n longs when we pass input attributes ang combinations.

Likelihood to Recommend

How address validator is used? IDD is used in data quality?

Sunil Reddy

Software Engineer in Corporate at Allegis Group (1001-5000 employees)

Vetted Review

10 years of experience

View profile

IDQ Review

Rating: 8 out of 10

March 10, 2014

Use Cases and Deployment Scope

In our organization that I was at, IDQ was being used only by a single department. We used IDQ to first help us standardize customer addresses and then eventually started using the matching capabilities to find duplicate records within our database. Before this product we used SQL statemtns to standardize data and find duplicates.

By using IDQ, it greatly reduced the time and effort to perform the above mentioned items.

Pros

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.

Cons

I wish some of the functionality was combined with PowerCenter, especially being able to create workflows, etc. and schdeuling them.

Likelihood to Recommend

IDQ was great at helping us cleanse our data and find duplcate information.

Verified User

Analyst (10,001+ employees)

Vetted Review

2 years of experience