Oracle Data Quality vs SAP Data Quality Management comparison

Oracle and SAP are both solutions in the Data Quality category. Oracle is ranked #15, while SAP is ranked #10. Oracle holds a 1.9% mindshare in DQ, compared to SAP’s 6.5% mindshare. Additionally, 88% of Oracle users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Oracle Data Quality

Read 8 Oracle Data Quality reviews

344 Views
168 Comparison Views

88% willing to recommend

SAP Data Quality Management

Read 2 SAP Data Quality Management reviews

628 Views
514 Comparison Views

100% willing to recommend

Oracle Data Quality

SAP Data Quality Management

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Executive SummaryUpdated on Jan 6, 2025

Oracle Data Quality and SAP Data Quality Management are competing products designed to enhance data reliability for businesses. Oracle seems to have the upper hand in pricing and customer support, offering a cost-effective solution with excellent integration and support benefits.

Features: Oracle Data Quality offers features like data profiling, cleansing capabilities, and seamless integration with Oracle's database tools. SAP Data Quality Management provides extensive data validation, enrichment features, and thorough data governance, making it ideal for large-scale enterprises. Oracle focuses on integration ease, while SAP emphasizes a wide range of data validation options.

Ease of Deployment and Customer Service: Oracle provides an easy deployment process and reliable customer service, ensuring smooth integration with Oracle environments. SAP Data Quality Management also supports strong deployment processes but often requires more initial configuration, offering integration across various systems. Oracle benefits businesses looking for simplicity, while SAP is suitable for complex data management needs.

Pricing and ROI: Oracle Data Quality is known for lower setup costs, appealing to companies prioritizing cost efficiency and a promising return on investment from streamlined operations. SAP Data Quality Management involves higher upfront costs, with long-term advantages from its comprehensive feature set, making it valuable for organizations focusing on thorough data management solutions. The difference is seen in Oracle’s budget-friendly setup versus SAP’s potentially high-value outcomes.

To learn more, read our detailed Oracle Data Quality vs. SAP Data Quality Management Report (Updated: January 2025).

Buyer's Guide

Oracle Data Quality vs. SAP Data Quality Management

January 2025

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Review summaries and opinions

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

Categories and Ranking

Oracle Data Quality

Ranking in Data Quality

15th

Average Rating

8.4

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

No ranking in other categories

SAP Data Quality Management

Ranking in Data Quality

10th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2025, in the Data Quality category, the mindshare of Oracle Data Quality is 1.9%, down from 2.7% compared to the previous year. The mindshare of SAP Data Quality Management is 6.5%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

Venkatraman Bhat

Deliver Head - Database and Infrastructure Cloud Services at Tech Mahindra Limited

Fast, has good extraction, validation, and transformation features, and provides good support

Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution.

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Rene Dorantes

IT Manufacturing Intelligence Chief at Productos Laminados de Monterrey

Scalable, stable, and offers good technical support

SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management. What I'd like to see from SAP Data Quality Management in the future is the integration of machines on the shop floor or a feature that connects shop floor devices. I'd also like a custom dashboard in the solution, though I wonder if that's available in the new version. The old version my company uses doesn't have that. Another feature I want in the next release of SAP Data Quality Management is better communication between the ME and the SAP systems.

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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 features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."

"With Oracle Data Quality, the most valuable feature is entity matching."

"I have found the most valuable features to be data cleansing and deduplication."

"Once it is set up, it is easy to use and maintain."

"We work with API standards or norms for internal applications, so it's essential for SSE to have tests and pass those tests according to the criteria, which makes SAP Data Quality Management very important for our products."

"Our primary use case is for us to inspect the results from the product and material, and for releasing or leaving the status of the product."

Cons

"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."

"If the length of time required for deployment was reduced then it would be very helpful."

"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."

"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."

"I would like for them to develop a feature to able to record all of our inspections; so all the data can go through SAP. It's not user-friendly or easy to get further analysis, so we mostly skip this step."

"SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management."

Pricing and Cost Advice

"The vendor needs to revisit their pricing strategy."

"The price of this solution is comparable to other similar solutions."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

33%

Manufacturing Company

Computer Software Company

University

Manufacturing Company

17%

Financial Services Firm

16%

Computer Software Company

14%

Energy/Utilities Company

12%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Comparisons

Informatica Intelligent Data Management Cloud (IDMC) vs Oracle Data Quality

Compared 100% of the time

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SAP Data Services vs SAP Data Quality Management

Compared 40% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAP Data Quality Management

Compared 35% of the time

SAP Information Steward vs SAP Data Quality Management

Compared 25% of the time

More SAP Data Quality Management Competitors

Product Reports

Buyer's Guide

Data Quality

December 2024

Download Oracle Data Quality product report

Buyer's Guide

Data Quality

December 2024

Download SAP Data Quality Management product report

Also Known As

Datanomic

SAP BusinessObjects Data Quality Management, BusinessObjects Data Quality Management

Learn More

Oracle

Video not available

SAP

Overview

Oracle Enterprise Data Quality delivers a complete, best-of-breed approach to party and product data, resulting in trustworthy master data that integrates with applications to improve business insight.

SAP BusinessObjects Data Quality Management, version for SAP solutions (DQM for SAP), enables you to embed support for data quality directly into SAP ERP,CRM and MDG applications. Start by entering a new customer, supplier, or partner record using the SAP ERP, SAP CRM , SAP MDG applications. Then this version of SAP BusinessObjects Data Quality Management software corrects components of the address, validates the address based on referential data sources, and formats the address according to the norms of the applicable country. This solution helps in avoiding the duplicate entities entering into your SAP ERP, CRM and MDG applications(supports different MDG data models for address validation and duplicate checks) and also helps in searching and improving your existing data.

Sample Customers

Roka Bioscience, Statistics Centre _ Abu Dhabi , Raymond James Financial inc., CaixaBank, Industrial Bank of Korea, Posco, NHS Business Services Authority, RWE Power, LIFE Financial Group,

AOK Bundesverband, Surgutneftegas Open Joint Stock Company, Molson Coors Brewing Company, City of Buenos Aires, ASR Group, Citrix, EarlySense, Usha International Limited, Automotive Resources International, Wªrth Group, Takisada-Osaka Co. Ltd., Coelba, R

Buyer's Guide

Oracle Data Quality vs. SAP Data Quality Management

January 2025

Free Report: Oracle Data Quality vs. SAP Data Quality Management

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