Informatica Cloud Data Quality vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Informatica Cloud Data Quality
Score 6.0 out of 10
N/A
The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.N/A
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
Informatica Cloud Data QualitySAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Informatica Cloud Data QualitySAS Data Management
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Informatica Cloud Data QualitySAS Data Management
Considered Both Products
Informatica Cloud Data Quality
Chose Informatica Cloud Data Quality
SAP Master data governance, Microsoft products, and Collibra
Chose Informatica Cloud Data Quality
Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of …
Chose Informatica Cloud Data Quality
There was not an evaluation period, since the product was already purchased by my company. I performed the installation and did the implementation.
Chose Informatica Cloud Data Quality
It was the only product I used for Data extraction and it works very well that I did not think of another option.
Chose Informatica Cloud Data Quality
Proven best-practice implementation methodology
Industry-leading data integration technology
End-to-end data migration services
Chose Informatica Cloud Data Quality
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, …
Chose Informatica Cloud Data Quality
IDQ has good integration with Informatica Powercenter and helps to clean and transform the data
Chose Informatica Cloud Data Quality
Informatica Data Quality provides more accuracy, adaptability, compatibility, and is performance-oriented. Integration with other applications is easy to achieve.
Chose Informatica Cloud Data Quality
Data Flux.
Chose Informatica Cloud Data Quality
We choose Informatica Data Qualtiy mainly because we had so many internal Informatica Powercenter Resources as well as it was easy to use and Analyst is user friendly tool for the clients / end users for quick glance at data
Chose Informatica Cloud Data Quality
SAP Info Steward. I have been using this tool in my past pharma organisation where the integration and target system was SAP. Though this integrates well but where far slower and had fewer quality checks than IDQ.
Chose Informatica Cloud Data Quality
Talend ETL provides a more integrated Data Quality tool but the choice for IDQ was completed before I started and company is entrenched with Informatica
Chose Informatica Cloud Data Quality
We looked at other products. It was an easy decision because we already had experience with Informatica PowerCenter.
Chose Informatica Cloud Data Quality
Informatica data quality is better than all the products today except that competitors have better report formatting. For example: Global ID and Talend have better profiling reports for business users ( charting.. etc). Informatica is lacking in this area.
Chose Informatica Cloud Data Quality
It was selected by senior management.
SAS Data Management
Chose SAS Data Management
The product is best when combined with the other products of the SAS suite. In particular, it's great for the preparation, analysis and display of the data if it is carried out with the products indicated above. When it is combined with products other than those of the SAS …
Chose SAS Data Management
SAS Data Management Platform requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres. Has almost all features present as compared to the alternatives we evaluated. On top of it, SAS offered statistical transformations and strong metadata …
Chose SAS Data Management
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
Chose SAS Data Management
Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end …
Chose SAS Data Management
Datastage might be the closest one. Being a full ETL tool, it's weird to compare both. Datastage might be more robust for extraction but it lacks the simplicity that the end users need for everyday data extract and analysis.
Chose SAS Data Management
SAS/Access can work well with MySQL. There are some coding differences between the two, for example how missing values are handled or rules for variable names. MySQL has simpler coding, but if you are familiar with Base SAS, it is not too difficult to learn. With SAS/Access the …
Chose SAS Data Management
SAS integration is not easy because there are various PAM related modules which require additional vendor involvement. Overall once all integrations are set up, it's a great tool and provides multiple options to users for running their model.
Features
Informatica Cloud Data QualitySAS Data Management
Data Quality
Comparison of Data Quality features of Product A and Product B
Informatica Cloud Data Quality
8.9
Ratings
2% above category average
SAS Data Management
-
Ratings
Data source connectivity9.30 Ratings00 Ratings
Data profiling9.20 Ratings00 Ratings
Master data management (MDM) integration8.90 Ratings00 Ratings
Data element standardization8.20 Ratings00 Ratings
Match and merge8.70 Ratings00 Ratings
Address verification9.00 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Informatica Cloud Data Quality
-
Ratings
SAS Data Management
8.3
Ratings
1% below category average
Connect to traditional data sources00 Ratings8.60 Ratings
Connecto to Big Data and NoSQL00 Ratings8.10 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Informatica Cloud Data Quality
-
Ratings
SAS Data Management
6.7
Ratings
20% below category average
Simple transformations00 Ratings6.10 Ratings
Complex transformations00 Ratings7.40 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Informatica Cloud Data Quality
-
Ratings
SAS Data Management
6.7
Ratings
17% below category average
Data model creation00 Ratings5.50 Ratings
Metadata management00 Ratings7.40 Ratings
Business rules and workflow00 Ratings6.60 Ratings
Collaboration00 Ratings7.00 Ratings
Testing and debugging00 Ratings6.10 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Informatica Cloud Data Quality
-
Ratings
SAS Data Management
7.9
Ratings
3% below category average
Integration with data quality tools00 Ratings7.60 Ratings
Integration with MDM tools00 Ratings8.20 Ratings
Best Alternatives
Informatica Cloud Data QualitySAS Data Management
Small Businesses
HubSpot Data Hub
HubSpot Data Hub
Score 7.7 out of 10
Skyvia
Skyvia
Score 9.9 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Informatica Cloud Data QualitySAS Data Management
Likelihood to Recommend
9.2
(0 ratings)
7.6
(0 ratings)
Likelihood to Renew
6.6
(0 ratings)
9.0
(0 ratings)
Usability
8.0
(0 ratings)
6.0
(0 ratings)
Availability
9.0
(0 ratings)
-
(0 ratings)
Performance
9.0
(0 ratings)
9.0
(0 ratings)
Support Rating
-
(0 ratings)
7.7
(0 ratings)
Online Training
10.0
(0 ratings)
-
(0 ratings)
Implementation Rating
10.0
(0 ratings)
-
(0 ratings)
Product Scalability
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Informatica Cloud Data QualitySAS Data Management
Likelihood to Recommend
We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways. At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.
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SAS/Access is well suited for companies who need to manipulate and analyze large databases and data-sets. It does the same thing as SQL, and if you already know basic SAS coding it is easier to pick up. SAS/Access works well with analyzing data from multiple data-sources at once, including large databases stored in external and virtual environments like Hadoop. Data can be easily reassembled from relational databases for use by the user. SAS/Access is not necessary if you are only pulling data from one database that you have the physical file for.
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Pros
  • Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
  • Character Set Mapping
  • Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports
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  • SAS supports the main database connection options that allow you to optimize the performance of your extracts and loads.
  • Simplicity of the syntax for a basic connection.
  • Ability to configure by an administrator in a BI environment so that all users can benefit from the connection without having to establish it by themselves.
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Cons
  • 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.
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  • It is a versatile product but sometimes difficult to use due to the very close link with the proprietary programming language where specific knowledge is required.
  • Compared to competitors on the market that offer the same functions for the integration perimeter, it is certainly very expensive.
  • It is very simple to use when combined with products from the SAS suite, less so it is being used stand-alone or integrated with other well-known brands.
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Likelihood to Renew
I gave a rating of 8 due to the fact that we use Informatica for both our data quality product and ETL product. Having both integrated makes it so much easier. Microsoft had a similar product of finding duplicates, but at the time it didn't seem mature enough. The usability also in IDQ was pretty easy to navigate and use.
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We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
Easy to use not only for developers but also business users
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The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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Reliability and Availability
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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No answers on this topic
Performance
Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.
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It worked as expected.
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Support Rating
No answers on this topic
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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Alternatives Considered
Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.
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Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end that allows us to transform and load our data quickly and efficiently programmer time wise.
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Scalability
Scalability works as expected and it is truly an enterprise system.
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No answers on this topic
Return on Investment
  • 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
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  • The platform enabled us to have a single repository of customers to run campaigns on.
  • Feedback from various campaigns is stored in a single database, which makes running A/B analysis easier.
  • Helped improve data quality due to SAS Dataflux being a part of the SAS Data Management Platform.
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ScreenShots