IBM InfoSphere Information Server vs. IBM watsonx.data intelligence vs. Informatica Cloud Data Quality

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

The IBM Watson Knowledge Catalog is most well suited for large companies. With large companies storing data for a long amount of time, this can be helpful to allow all team members to find documents with ease. It would be less appropriate for storage that is deleted very often or does not needs to be saved for long amounts of time.

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

• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

Incentivized

• Data discovery.
• Technical Data Lineage.
• Business Data Lineage.
• Data .
• Multiple Data Catalog Management.
• Creation of Governance Rules.
• Data Masking.

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.

• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

Incentivized

• I think an industry-specific data catalog service will be good.
• Effective alignment of IBM consulting services and bringing in an Industry point of view will be great.
• Effective reach out like roadshows, etc. will be good.

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.

• Scale of implementation
• IBM techsupport

Incentivized

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 very easy to use and very intuitive Es muy sencilla de utilizar y muy intuitiva

Incentivized

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

DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

The IBM Watson Knowledge Catalog is a great amount of storage for the price. It is easily accessed by all users in the company. It provides great search features and clear pathways to locate documents. This is great for the team and our client when needing access to a specific document.

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

• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.

• The negative note: is that it needs to have a very secure cloud infrastructure and with its data well defined for integration with other databases.
• The positive point: allows for quick data discoveries aiding a quick implementation of privacy programs.

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