IBM Log Analysis with LogDNA vs. Informatica Cloud Data Quality

IBM Log Analysis with LogDNA is well suited if you are using other IBM cloud product ecosystems. It's very mature and supports HIPAA-compliant configurations if you need to store PI/PHI data. We particularly use it for audit requirements but understand the limitation with the retention period is for 30 days only. Also you need to configure if your IBM cloud service doesn't have any log collection or report tool. Log collection agents are widely supported for most of infrastructure in cloud.

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

• Easier integration with other IBM cloud resources
• Flexible access control setup using RBAC
• Supports other infrastructure as well, like Kubernetes and VMs

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.

• Ability to create KPI charts and metrics dashboards out of the box

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.

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

If you use other IBM product ecosystems, IBM Log Analysis with LogDNA is the obvious choice, as it supports seamless integration and better access control with IBM cloud access group setups. IBM Log Analysis with LogDNA was flexible and has wide support for various infrastructure implementations and is also controlled by the same IAM access setup. It can be configured for any IBM cloud services or platform logs or for infrastructure by installing the agent.

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

• Most of IBM cloud services support easier integration for log analysis.
• We are able to achieve compliance with various audit log reports, which improves governance and control over various cloud resources we have.
• Also IBM Log Analysis with LogDNA helps in troubleshooting and analysis for application logs in real time. This helps with improved issue resolution timings.

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