CData Sync vs. Informatica Cloud Data Quality

Evidently, CData Sync is an excellent middleware tool that is perfect for syncing data between systems. It is especially suitable and works well on SQL servers, DB2, MySQL, and Snowflake, and some of their brothering domains. However, it is a limitation in working with Sage 50 API. But if it is extracted with ODBC, it works well.

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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.

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• UPSERT
• Friendly interface

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• 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.

• Although efficient for SQL servers and MySQL, as well as Snowflake. It is not strong for other database engines, and an upgrade on this would do a lot.
• The installation process is manual as opposed to the cloud installation it should be.
• A feature of syncing auto increment ID key, that will help in existing data management.

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• 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.

It is easy to setup and use

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Easy to use not only for developers but also business users

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

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

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Tableau is another similar software tool, unlike CData Sync, rather transforms data into actionable insights. While CData Sync works with automation, Tableau uses a drag box on its AVA, which in turn slows the work speed on the syncing of data. Over the years, I enjoyed the friendly and customizable option of CData Sync over Tableau's.

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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.

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• Positive: Easy way to bring data for our DWH
• Negative: Frequent issue in CData Sync Server

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• 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