Oracle Data Quality Reviews

We're mostly using Oracle Data Quality during the ETVL process, or to make sure that there's one source of truth and that there's no redundancy at all. We're also using the solution for quality assurance and data governance. It's part of the cleansing activity for enterprise data, not only for a data warehouse but also for Data Lakehouse. Through Oracle Data Quality, you'll get data from multiple sources, plan it then present it with an analytics layer.

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.

We are a system integrator and software solutions company, and Oracle Data Quality is one of the solutions that we use to provide services.

In a multiple-system integration scenario, there is data flowing between different systems. Oracle Data Quality is used to establish a single source of truth. It is also used for new system integration and new application integration.

Customers are really keen to use this product for profiling, auditing, synching, and matching.

This system can handle any kind of data, whether it is customer data, product data, personal data, or financial data.

It integrates well with third-party applications.

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

We use it in the university fundraising industry. Once students graduate and start giving to the university, they become donors. Then, we need to maintain their giving history. Giving is quite complicated. You can make a pledge, and your company can make a matching gift. We need to make sure that all that type of information is in our system.

When they make a gift to online, we want to make sure to load the data into our Advancement database right away or as soon as possible. We don't want to delay a week, for example, and send them a gift received acknowledgement.

With Oracle Data Quality, the most valuable feature is entity matching. For example, I have a John Smith in our system and another John Smith makes a gift online, and there's no unique identifier, like an ID number, to link those two together. So, we need to come up with a solution to match them up.

I want to have matching algorithms set up to make sure that the data from different systems will come in and also become unified or have a consolidated record for John Smith. You want to have a 360 degree view of this record.

We are using this solution for data quality management.

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

The most valuable features of this product for me:

1. Address verification
2. Integrated data profiling, auditing, and cleansing.

We were able to automate our data profiling tasks that enabled us to identify and establish data quality rules and standards more efficiently. Since the rules are set up and integrated within the tool, it also facilitated an improvement in our data quality audit/validation and cleansing efforts. The address verification capability is also handy i.e. in making sure that our Customer and Supplier master data is accurate.

Synchronization of Contact / Account data is most valuable to the client.

The quality of data has vastly improved & our business intelligence reports are accurate in real time.

Additional examples:

1) Stateless – that means no synchronization of Contact / Account data is needed between Siebel and OEDQ. If for example a new contacts gets created – it will be possible to match this new contact immediately. There is no lag time for the synchronization between both.

2) Fully configurable matching process. In OEDQ a matched contact or account – the rules which are applicable while matching can be identified. So a score of 95% can be explained in such a way that a contact was found based on an exact match but with a different phone number.

Data Cleansing, Profiling, Matching, Customizable platform to meet anyone's needs.

Identifies the data anomalies and correct them. Finds the duplicate data with the entire enterprise Customer/Product data and merges them to make a single Customer or Product unique across the enterprise.

Ease of management within Oracle Data Integrator (ODI) and effectivity of EDQ Director

OEDQ helped us to define Data Quality issues from a business perspective by business users and ability to manage those issues within our ETL tool (Oracle Data Integrator - ODI).