The Collibra Platform is a cloud-based data governance platform from the company of the same name in Brussels, enabling users to gain visibility into their data, collaborate intelligently and enable users to easily access trustworthy data, automate processes, manage compliance and, ultimately, make data meaningful.
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Informatica Cloud Data Quality
Score 6.8 out of 10
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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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Talend Data Fabric
Score 10.0 out of 10
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The Talend Data Fabric helps organizations to achieve and maintain complete, trustworthy, and uncompromised data, so that they can stay in control, mitigate risk, and drive value.
Informatica data quality is better than all the products today except that competitors have better report formatting. For example: Global ID and Talend have better profiling reports for business users ( charting.. etc). Informatica is lacking in this area.
Talend ETL provides a more integrated Data Quality tool but the choice for IDQ was completed before I started and company is entrenched with Informatica
Talend Data Fabric
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Features
Collibra Platform
Informatica Cloud Data Quality
Talend Data Fabric
Data Quality
Comparison of Data Quality features of Product A and Product B
Collibra is well suited where you have multiple reporting environments and multiple source systems. Collibra works well in our environment because we can delegate roles and administration to departments or it can be used in a centralized environment. The ability to customize attributes and assets as well and integrate using the rest api is very important to us.
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.
Truly trusted contact center where the effective solution is always guaranteed. It is not a one-off fix to a specific data integration or management problem. It is a permanent and scalable solution to manage all of your data under a unified environment. Easy to use, great performance, used it for our internal data warehouse. Easy to build and connect to our data sources such as Salesforce, Netsuite, and Marketo.
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.
It supports a wide variety of connectors (Systems/endpoints)
It provides great flexibility for developers as it not only has a lot of predefined ready to use the function but also provides the ability to use complex java code within the platform. Great tool if you have good developers available.
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.
At this moment the usability of Talend Data Quality is optimal, too bad I cannot say the same in the first three months, it was always a problem due to its steep learning curve, but what matters is being able to use it effectively at this precise moment.
Talend Data Quality gave us direct help in the learning process and prevented us from taking many more months to adapt and I appreciate this from the heart, I think that thanks to the support we can have very detailed reports that help increase the use of Talend Data Quality in the company.
Collibra offers more features [than alternatives] and is easy for business users to use. We did a proof of concept with Collibra using the Cloud service that allowed us to kick the tires and get a comfort level before we made the investment. At the time of our purchase the market was very immature and is continuing to evolve.
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.
The engine with which it works to process a lot of information is striking, the comparison also being the connectors it has for different RDBMS, which other tools do not count as they are GNU licenses or community editions. The friendly and intuitive environment is what catches the eye. that's why I choose Talend over any other tool
ROI is hard to measure because there are so many soft benefits that come from the tool. We do have a variety of metrics that we track using Collibra to better gauge the maturity of data governance.