Oracle Enterprise Data Quality - versatile and easy to use
May 20, 2019

Oracle Enterprise Data Quality - versatile and easy to use

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Oracle Enterprise Data Quality

It is being used to identify and manage duplicated data across its customer database and write rules to filter out bad customer information.

In other clients, it was used across the entire organization to manage product data and a huge amount of customer-facing SKUs.
  • Simplifies the data quality aspects.
  • Visualizes data flows.
  • Provides many pre-built processes that are very powerful.
  • Quickstats overview is an amazing tool to quickly understand how bad the data currently is.
  • Updates are few and far between as this has transitioned to the Cloud and is the core engine for DIPC (Data Integration Platform Cloud).
  • Needs governance around the tool if multiple people are running reports (e.g. if someone is running a process, it locks out other users).
  • Positive - it is required for clients and for us to understand how bad the data really is - it allows for iterative review and improvement of creating data quality rules
  • Positive - the ease of use and visual review allows us to quickly create the rule set and show (in the tool) how it works. We save a lot of time by not creating powerpoints to explain what is happening.
Oracle Enterprise Data Quality seems very well suited for managing large data sets. Its capabilities are very strong and I've seen it work in many industries and across both Product and Customer Data.

Less appropriate scenarios are very small data sets.

On the features - address verification is not included - but can be connected to other cloud services and needs additional licenses.

Oracle Data Quality Feature Ratings

Data source connectivity
Data profiling
Master data management (MDM) integration
Data element standardization
Match and merge