Ataccama ONE vs. Azure Data Catalog vs. Informatica Cloud Data Quality

Usage for enterprise wide data management and governance across wide range of user group. Ataccama ONE enables achieving higher data quality amongst the data products. It is a powerful platform that supports integration of several checks on different data sets that can be also consolidated in reports later on. Data discovery works quite fast and easy.

Incentivized

Azure Data Catalog helps us solve data discovery problems
brilliantly. Our organization created a single source of truth for our data,
which allowed us to develop BI and data science solutions. We can drag tables
or data sources to manage workflow. Some of the more complicated data normalization
or standardization issues need to be simplified, and I'd like to see that
happen.

Incentivized

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.

Incentivized

• It is one of the leading data quality tools in the industry, in our opinion.
• Offers free data profiling.
• Integrates with other tools for complete end-to-end lineage.

• It's easy to use and implement.
• Ownership of the data.
• It's helpful for all businesses.
• Policy on data preservation.
• It can utilize various data sources.
• Data management is secure and simple.

Incentivized

• 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.

• Performance in loading
• Reduction of pop-up messages

Incentivized

• Maintenance and creation of documentation for data sources takes a lot of time
• One cannot connect to data using a client's app unless they know the locus of the data source.

Incentivized

• 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.

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.

One of the key factors in our choice to onboard Ataccama was its usability - general end users have everything at their fingertips, it is not difficult for IT developers to setup the tool, and it has been an overall pleasure.

Easy to use not only for developers but also business users

Incentivized

The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server

Incentivized

Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.

Incentivized

Support has been excellent to date - very user friendly and knowledgeable to help support our needs and issues as they arise.

Ataccama ONE is a designated tool for Data quality monitoring. Supports end to end. Quite easy to deploy. Alteryx is more about coding or almost as complicated while Ataccama ONE is a bit easier to use. Different interfaces. Many views automatically available for data sets in Ataccama ONE. Output is vizualized in the tool. While more data transformation is required in Alteryx.

Incentivized

Azure Data Catalogue was chosen for

• Microsoft's customer service and expertise
• Experience with Azure Cloud Solutions
• Reviews from peers on functionality and performance
• Product roadmap
• Overall costs

Incentivized

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.

Scalability works as expected and it is truly an enterprise system.

Incentivized

• Less data inconsistencies in the system enable processes to run smoother without interruptions

Incentivized

• Azure platform makes it easier for us to register & catalogue all available information easily. This way when the customer actually made a sudden request or they want to access sensitive information on their own, the data is readily presented to them. Needless to say we use this mined and catalogue data for a variety of inhouse training and other improvement initiatives.

Incentivized

• Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion
• Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production
• Employee efficiency is increased exponentially due to more automated, customized tool