Dataloader.io vs. Informatica Cloud Data Quality vs. Progress DataDirect

Replacing data. If we've put something in a category or a bucket that is no longer named that anymore because we've evolved with the times and we want to rebrand everything, it makes it way easier to do a quick import with the new terms.

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

Hybrid Data Pipeline lets users consume or share data in can timely and compliant manner regardless of the application they use or the location of the data. It has defined a stringent set of policies and practices around product development and distribution. Enables customers to consume their data in your application using their BI tool of choice.

Incentivized

• Extracting Salesforce attachments in original file format! I do not know of a tool that can do this better, or more efficiently! This is a huge benefit to companies that would like to extract attachments from Salesforce for tasks like data migrations.
• Cross-object data extract within one file. You can pull data from related objects as long as there is a populated lookup from the object you are extracting, to another object (Child or Parent).
• UI is simple and requires very little to no training. Given the acquisition of Mulesoft by Salesforce, I would not be surprised if DataLoader.IO is rolled out as the new global data loading tool for Salesforce.

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.

• Providing JDBC connectivity to CRM applications
• Raw data integration
• Customer support

Incentivized

• At the moment, I can't find a way to rename jobs. This would be useful to organize what was previously created hastily by techs in a rush.
• A preview of the job, especially upserts, would take a great deal of stress away from some of us (especially those who are not so confident in their ETL practice).
• A native vlookup equivalent may be a welcome addition.

• 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.

• Seamless data access for BI and Analytics.
• Helps you comply with industry standards.
• Cloud and On-premises Data Access with Hybrid Data Pipelines.

Incentivized

It is easy to use and doesn't require a security token, so I enjoy using it. It also doesn't require any download or installation, which is sometimes a blocker to gettingthings done if the company has limits. also, the dataloader.io is easy for other people to pick up, so others can have visibility into the data jobs that have occurred

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.

Dataloader definitely skews towards a more technical userbase. Users should be adept at manipulating data in spreadsheets and decipher JSON formatted error messaging. Additionally, there is a good amount of time need to set up the environment to map to the pertinent fields we are trying to adjust. While I would not recommend the typical account manager to use Dataloader, a typical operations manager should have no issue.

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

Dataloader is made for updating, inserting, and deleting of contacts. For these operations this tool is excellent.

Incentivized

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

Incentivized

The utility itself is very self-explanatory and has enough information to guide you through the process. It has an intuitive experience for those familiar with data loading/exporting utilities. Outside of this, they have a Zendesk help center to log support requests and provide documentation to help guide you troubleshoot any issues that may be occurring.

Incentivized

I have used salesforce inspector also for operations like import and export of data from custom objects but it doesn't work well when you have data in huge numbers. Instead of using Salesforce Inspector, one should go for Dataloader.io if the number of records is huge to be dealt with.

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.

Easy to use with JDBC interface, detailed debug logs for troubleshooting, and easier audit with detailed log. Cost of ingestion is relatively cheaper

Incentivized

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

Incentivized

• HUGE time saving. When we need to clean or review data, we used to have to do it line by line. This can do the work within excel and make cleanup/management an afternoons work as opposed to a week.
• Rollback what you did/change/deleted is relatively simple if you remember to back up the data you are manipulating.

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

• Create custom data access and security policies at a user level.
• Integrate HDP into your app seamlessly with management and administration API's.
• Hybrid Data Pipeline service can be deployed on multiple modes behind a load balancer.

Incentivized