Informatica Intelligent Data Management Cloud (IDMC) vs Melissa Data Quality comparison

Informatica and Melissa are both solutions in the Data Quality category. Informatica is ranked #1 with an average rating of 7.8, while Melissa is ranked #8 with an average rating of 9.0. Additionally, 93% of Informatica users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Informatica Intelligent Dat...

Read 181 Informatica Intelligent Data Management Cloud (IDMC) reviews

3,248 Views
2,421 Comparison Views

93% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

530 Views
292 Comparison Views

95% willing to recommend

Informatica Intelligent Dat...

Melissa Data Quality

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Executive Summary

We performed a comparison between Informatica Intelligent Data Management Cloud (IDMC) and Melissa Data Quality based on real PeerSpot user reviews.

Find out in this report how the two Data Quality solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Informatica Intelligent Data Management Cloud (IDMC) vs. Melissa Data Quality Report (Updated: October 2024).

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC) vs. Melissa Data Quality

October 2024

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Categories and Ranking

Informatica Intelligent Dat...

Ranking in Data Quality

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

181

Ranking in other categories

Data Integration (3rd), Business Process Management (BPM) (7th), Business-to-Business Middleware (3rd), API Management (7th), Cloud Data Integration (3rd), Data Governance (2nd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (4th), Product Information Management (PIM) (1st), Data Observability (2nd)

Melissa Data Quality

Ranking in Data Quality

8th

Average Rating

8.4

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Data Scrubbing Software (4th)

Featured Reviews

Raj Sethupathi

Data Integration Consultant GCP/AWS at Infogrators Inc

Offers profiling and address standardization but can be complicated

Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process. Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash. Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.

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GaryM

Data Architect at World Vision

SSIS MatchUp Component is Amazing

- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution is straightforward."

"The capability of the tool to scan and capture the metadata from a variety of sources is one of the capabilities that I find most useful. The central repository into which it is going to put that captured metadata is the best."

"Data integration is the most valuable feature. The ability to connect to any of the sources and enterprise applications makes our lives easier."

"The most valuable feature is its ability to extract metadata from various sources- be it an old SaaS application or the latest cloud application."

"The solution's technical support is pretty good, especially since the turnaround time is good."

"The most valuable features are data quality, data integrate transformations, match-merge, and a few MDM solutions we build into data quality transformation."

"It is easy to create REST-based interfaces of the master data objects."

"The mass ingestion functionality and the elasticity of the solution are great."

More Informatica Intelligent Data Management Cloud (IDMC) pros

"Provides quality accurate data that our downstream solutions depend on."

"Ability to validate addresses, make corrections to address."

"We use their GeoPoints to get the most precise, rooftop level geocoding."

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."

"Services for all manner of data-driven organizations, no matter their size or budget."

"Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."

"We use a Melissa API to access the data, so it easy to use, accurate, and fast."

More Melissa Data Quality pros

Cons

"Right now, although they offer some templates, I would want more templates available to be imported."

"The scalability is tough."

"This solution is hard to set up and its interface is not user-friendly. It's also not as stable, and the technical support takes a lot of time to solve simple problems."

"The cloud version of the Informatica, it's a very substandard product. They might say it's enterprise-ready but it's not at all ready. They need to add more features, such as improved data replication features. If you look at other tools, such as Matillion they are now cloud-native and flexible. Additionally, Informatica Cloud Data Integration should have a good migration strategy from Informatica PowerCenter to Informatica Cloud Data Integration."

"The advertising makes promises about data analytics that it does not keep."

"The product isn't mature enough to provide suitable connectors to various data engines."

"The data discovery isn't that good yet for Salesforce. We have another tool that we use for this. It may be a problem because Salesforce on the cloud."

"Informatica Axon does not provide complete transparency about the level of detailing you need and the logic used in ETL."

More Informatica Intelligent Data Management Cloud (IDMC) cons

"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."

"Many issues, sometimes I have to completely log out and start over."

"Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes."

"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."

"I wish there was a way to do a "test run" and see what a particular format will give you."

"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"

"The SSIS component setup seems a little klunky."

"Needs to validate more addresses accurately."

More Melissa Data Quality cons

Pricing and Cost Advice

"The pricing is quite flexible."

"It's an expensive solution."

"The price of Informatica Cloud Data Integration could be reduced."

"Informatica Axon is expensive."

"We switched to Informatica PIM because it was cheaper than the Oracle solution. It is cheaper initially, but they will bundle it later. This is what happens in the industry."

"I rate the product's pricing a five on a scale of one to ten, where one is cheap and ten is expensive."

"My understanding is that Informatica is quite expensive compare to other tools that are available in the market."

"It is expensive. That's probably the biggest drawback. The business has heartache paying the license, but that's mainly because they don't realize what value it brings. The key thing about the MDM solution is that it is in the backend, and no one sees what it is actually doing. You don't know it is a problem until it is not there."

More Informatica Intelligent Data Management Cloud (IDMC) pricing and cost advice

"You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle."

"It is affordable."

"It's affordable."

"They were willing to work with our preferred vendors, though it involved extra steps to get the license."

"Melissa pricing is competitive."

"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."

"Depends on situation. We prefer to have data onsite, but some might prefer web access."

"Generally, the cost is ROI positive, depending on your shipping volume."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

13%

Manufacturing Company

10%

Insurance Company

Manufacturing Company

14%

Financial Services Firm

11%

Insurance Company

10%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How does Azure Data Factory compare with Informatica Cloud Data Integration?

Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...

See all answers

Which Informatica product would you choose - PowerCenter or Cloud Data Integration?

Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...

See all answers

What are the biggest benefits of using Informatica Cloud Data Integration?

When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...

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Comparisons

Informatica PowerCenter vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 9% of the time

Azure Data Factory vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 7% of the time

Reltio Cloud vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 5% of the time

AWS Glue vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 4% of the time

Microsoft Purview Data Governance vs Informatica Intelligent Data Management Cloud (IDMC)

Compared 4% of the time

More Informatica Intelligent Data Management Cloud (IDMC) Competitors

Experian Data Quality vs Melissa Data Quality

Compared 31% of the time

More Melissa Data Quality Competitors

Product Reports

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC)

November 2024

Informatica Intelligent Data Management Cloud (IDMC) report

Download Informatica Intelligent Data Management Cloud (IDMC) product report

Buyer's Guide

Melissa Data Quality

November 2024

Download Melissa Data Quality product report

Also Known As

ActiveVOS, Active Endpoints, BPM, Address Verification, Persistent Data Masking, Cloud Test Data Management, PIM, , Enterprise Data Catalog, Data Integration Hub, Cloud Data Integration, Data Quality, Cloud API and App Integration

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Informatica

Melissa

Overview

Informatica Intelligent Data Management Cloud (IDMC) is a robust platform used by banks, financial institutions, and health sector organizations for data management, governance, and compliance.

IDMC provides comprehensive tools for data discovery, profiling, masking, and transformation. It supports Salesforce integration, real-time data streaming, and scalable data management solutions. Health organizations manage national product catalogs while financial entities focus on data protection and regulatory compliance. Its intuitive interface, flexible features, and robust tools make it valuable across sectors, though enhancements in data integration and human workflow are being sought.

What are the most important features?

Data discovery: Facilitates identifying and understanding data sources.
Data profiling: Analyzes old databases for data quality.
Data and platform masking: Ensures data protection.
Salesforce integration: Seamless connectivity with Salesforce.
Mastering data: Centralizing and standardizing data.
UI intuitiveness: User-friendly interface.
Feature map flexibility: Adapts to user needs.
Business glossary creation: Defines business terms.
Data lineage: Tracks data flow and transformations.
Automation: Streamlines data processes.
Enterprise data cataloging: Organizes extensive data assets.
Scalability: Supports expanding data requirements.
Easy setup: Quick deployment process.
Bulk upload: Efficiently handles large data volumes.
Customizable data management: Tailors data solutions.
Real-time data streaming: Manages live data streams.
Integration with Hadoop and NoSQL: Connects with big data platforms.

What benefits and ROI should be considered?

Regulatory compliance: Ensures adherence to regulations.
Data protection: Safeguards sensitive information.
Enhanced data quality: Improves accuracy and reliability.
Centralized data: Consolidates data for better management.
Process automation: Reduces manual tasks and errors.

Banks and financial institutions use IDMC for data masking, transformation, and compliance, while health sector organizations leverage it for national product catalogs. Industry applications focus on automating business processes, centralizing data, and managing data catalogs to meet regulatory demands and ensure data protection.

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Sample Customers

The Travel Company, Carbonite

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

Buyer's Guide

Informatica Intelligent Data Management Cloud (IDMC) vs. Melissa Data Quality

October 2024

Free Report: Informatica Intelligent Data Management Cloud (IDMC) vs. Melissa Data Quality

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