Informatica Cloud Data Quality Reviews and Ratings
Rating: 6.6 out of 10
Score
6.6 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.
IDQ is being used across our organization. Specifically, we use IDQ for contact and address validation. As part of the sales and marketing domain, we need to enrich data for better campaigns. IDQ is a key player in accomplishing this process for us. We are using the Address Doctor engine for our standardization. Address Doctor standardizes contacts and addresses.
Pros
IDQ'S Delivery Point validation is very powerful and many competitive tools don't provide this
IDQ supports WGS 84 geocoding standards
IDQ validate addresses up to to a very high degree of accuracy
IDQ is used by a department at my organisation to ensure and enhance the data quality. We started with address standardization and now it had been brought to 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 was affecting sales projections and estimates.
Pros
Better compatibility with PowerCenter. This way you can do mix- match with existing mapping rules in ETL and also value add with quality check and exception reporting
Address Doctor - Optimize the accuracy of your company's global address data by using the only software with all five postal certifications in one engine. It parses, cleanses, and standardizes it, then appends accurate geocodes and consumer segmentation codes for specific countries
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.
Cons
I think its high time Informatica integrated all tools like PowerCenter, IDQ, IDE, powerexhange into one package will simplify development and maintenance
Likelihood to Recommend
Customer address mismatch and bad quality is a global mess. I have strong knowledge of this topic and have had consistent issues with the customer addresses, names product names, codes, statuses etc. Address Doctor and duplicate check was the biggest boon for me and my organisation to overcome this hurdle. Before using IDQ, it was all manual and it was very difficult and time consuming which added a lot of cost to the projects.
We are sourced from heterogeneous relational database's and also from legacy systems like SAP and SAP BW for our data integration project. After addressing multiple bugs and errors on the production data, we learned that Data Profiling and Data Quality was really missed during the analysis stage. 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 guys, it helped us with quite a few production tickets. It also helped us with best end user experience. We are still on top of the learning curve using IDQ, but we are holding up strong with it as is now.
Pros
Correcting error prone manual data entry across the organization, correcting formulas, rules and methods. Understanding the data properly first to begin with. Improving and approving the accuracy overall.
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.
IDQ decreased the capital on Production support and QA time especially.
Cons
I did not spend any time researching the tool for improvements, but the interface with Power Center will me more interactive and connected to the developers.
Likelihood to Recommend
How the data is created and transformed today for the current business Process.
My experience is with Data Transformation and i believe it is very critical. IDQ have / has abilities to standardize the required formats and elements to include, integrate and enhance conformity.
how can the value be added retaining integrity.
Improves Parent Child relationships and Reduces Orphans scenarios. The relative information is always available and validated.
How the data can be transformed or processed for multiple areas with END to END consistency.
Typically it depends on the Data Sources, But end to end consictensy in any ETL can very well be enhanced with multiple functionalities and transformations from IDQ.
Informatica Data Quality is being used to monitor the overall qualtiy of the data organization wise. We have created mapplets which filters / ensures the data quality has been met and shows how much percent of hte data has passsed Company Data Quality policies and how much percent data has failed also it provides detailed granular level view of the data which has not met data quality standarads.
Pros
It can profile the data pretty well and provide you overall statistics of the data quality based on your defined rules... It can show you in the graphical representation as well by showing that if the data qualtiy has dropped then it could display the bar in RED
It can be useful for validating the address and telephone numbers as well as SSN numbers for example if someone has mistyped SSN or not provided SSN or may be phone number format is wrong then It can help you to highlight as well as drilldown and figure it out for which particular record the data has not met the data quality standard.
Cons
Its awkward to go back and forth from Informatica Developer to Informatica Analyst to view and run and edit the profiles or scorecards that we create. Also tags can be enabled and edited from analyst or developer only (something like that) Tags on the scorecard or profiles should be fully accessible from the Informatica Developer since because developer is the main point of development... I personally consider that Analyst is more like Client side tool on which we should not provide Tag editing features on any scorecards otherwise any user can go to scorecard and change the tags and that might create confusion for another user.
Likelihood to Recommend
It is well suited for being an intermediate tool while creating MDM so it could fit in the scenarios like while pulling the data from OLTP and then pass it through the IDQ for data validation such as address and SSN validation and then finally load the clean / validated data to the MDM Hub database.
VU
Verified User
Consultant in Information Technology (501-1000 employees)
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.
Pros
Address Doctor-Optimize the accuracy of your company's global address data by using the only software with all five postal certifications in one engine. It parses, cleanses, and standardizes it, then appends accurate geocodes and consumer segmentation codes for specific countries
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.
Better compatibility with powercenter. This way you can do mix- match with existing mapping rules in ETL and also value add with quality check and exception reporting
Character Set Mapping
Cons
I think its high time Informatica must integrate all tools like powercenter, IDQ, IDE , powerexhange into one which will simplify development and maintenance
Likelihood to Recommend
Customer address mismatch and bad quality is a global mess. I have strong knowledge and consistent issues with the customer addresses, names product names, codes, statuses etc. Address Doctor and duplicate check was the biggest boom for me and my organisation to overcome this hurdle. Before using IDQ, it was all manual and it was very difficult and time consuming which added so much cost to the projects.
VU
Verified User
Consultant in Information Technology (10,001+ employees)
IDQ was purchased at Apollo about a week before I was hired and my first primary duty was to get the tool up and going (infrastructure, install, config, staff). It was used to present quality scorecards to data stewards/owners
Pros
The tool was designed with the intent to link quality to the data steward/owner
The functionality from the ETL allowed for great flexibility when designing quality filters
Cons
The tool is a profiling tool that is completly disconnected from ETL flow so no realtime processing
The sheduling is apalling
There is no alerting; but I guess if you're only profiling data, there is not much point
Likelihood to Recommend
The tool would be fine if you are looking to base your data quality on profiling data weekly
We use Informatica Data Quality IDQ to validate customer and vendor addresses and to insure there are no duplicates. We also use it to verify consistency in product descriptions.
Pros
Each night we process every customer, vendor and product. We generate reports of exceptions and these are distributed to the stewards of the data to allow them to correct issues.
IDQ has extreme flexibility in how you create rules to identify what is out of compliance. No matter how complex your rules, it will likely handle it in an easy to program user interface.
Cons
It is not the cheapest solution, but at this time I believe it is the best solution. Knowing your customers and accurately managing them justify getting the best product.
Likelihood to Recommend
All companies have problems with duplicate entries in customer databases. This tool allows you to easily consolidate the duplicates.
Customer creation process - using web services for matching and address cleansing. Managing exception record management for both bad and duplicate record management. Currently using across the organization for scorecarding to cover DQ problems.
Pros
It's a great tool for profiling and score carding and cleansing bad data
Matching, standardization, address doctor, exception record management
Data services, web services, entity discovery, show lineage
Cons
Scorecard export functionality for bad records - and it only displays the first 100 records
There are no filtering conditions on scorecarding
In IDD we cannot import bad record tables or duplicate records table as we did it in 9.1
Profiling results should be displayed in charting mode, as with other tools
Likelihood to Recommend
Quality check can be done across all environments but my suggestion would be that before the start of any project, the source systems must be analysed for data quality. It is much more cost-efficient to do data cleanup before the project begins.
To implement data quality to meet compliance, IDQ was selected as the tool. Currently it is being used by one department, and will gradually be used across other departments.
Pros
IDQ does a good profiling, and it is easy to create rules.
Use IDQ ONLY if you use Informatica Power centre as the ETL tool, else IDQ is not very effective. The major work of IDQ is called standardization, in which business can correct the data and repost the corrected data in a file, But it is possible only if IDQ is integrated with Power centre.
There is a scorecard that provided good graphical interface to the results.
Cons
The issue was on how badly it was implemented. All the files were uploaded to IDQ server using same file name minus the date. So IDQ wasnt able to display the historical metrics.
The performance was too slow, with multiple users.
While it is easy to create rules, you cannot view the actual code in the rules if it is written by someone else.
Likelihood to Recommend
Use IDQ only if you use Informatica as Power centre. In that case, IDQ is strongly recommended. If not, do some POC first
VU
Verified User
Consultant in Information Technology (10,001+ employees)
