Oracle Enterprise Data Quality Reviews and Ratings

Use Cases and Deployment Scope

Oracle Data Quality remains to be a proficient, substantial, and advanced data support program, that ensures there is security throughout the database, the analytical platform is digitized, and a secure cloud area. Further, the elimination of redundant data and any duplicates makes Oracle Data Quality more demanded. The cleansing of the entire data content acts as a transformational solution that fosters quality support and digitizes every activity. Lastly, there is data connectivity, address affirmation, and reputable communications.

Likelihood to Recommend

Oracle Data Quality is suitable for managing and evaluating the available sales database, which acts as the fundamental solution in controlling the market share. Further, Oracle Data Quality creates a detailed profile, of any database, which gets accessed in case there is fundamental analytics or data verification. More so, every data or client's information gets the required verification, which is a rational way of remaining relevant and extra competitive.

Use Cases and Deployment Scope

We deal with lot's of customer data and we are using Oracle Enterprise Data Quality to identify and manage duplicate data across our customer database. The software makes it easy to improve data quality. After putting th the data in order, we backup the data to be used when contacting our client or when running marketing campaigns. The software has made it easy to have a single data source containing clean and verified data.

Likelihood to Recommend

When it comes to cleaning large data, for instance customer data, Oracle Enterprise Data Quality comes in handy and offers best features that makes it easy to clean data and visualize any flows.

Use Cases and Deployment Scope

We use OEDQ to help improve the data quality of millions of lines of customer data with terrible addresses. It was initially used by only my department-- Data Government-- to build Customer Master Data, and now gradually to provide information back to the IT department and Sale Operation team. Our goal is to have a single source of truth of Customer Data across the whole company based on OEDQ and Oracle CDM Cloud.

Likelihood to Recommend

Implement OEDQ if your company has massive amounts of data that is poor quality.

Use Cases and Deployment Scope

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.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

Oracle Enterprise Data Quality (EDQ) is used to identify and correct data quality issues concerning names, addresses and master data causing reporting issues.

Likelihood to Recommend

EDQ is well suited for situations in which there are multiple entries of a single customer, product or site causing downstream reporting issues. It does great in transforming, standardizing, matching and merging these discrepancies.

Use Cases and Deployment Scope

Oracle Enterprise Data Quality (OEDQ) helped my organization 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).

Likelihood to Recommend

<ul><li>Ease of adding localized and customized data quality formulations (for instance asking for Turkish Citizenship Number from governmental web service and checking whether data is the same with the output).</li><li>Finding the "golden record" from the duplicated records.</li><li>Adding and/or merging missing information from different data sources.</li><li>Using patterns and statistical functions to complete the data.</li><li>Address verification (can be localized).</li><li>Parsing of combination of records.</li><li>Enriching required data from free text (story told) inputs.</li></ul>

Use Cases and Deployment Scope

We use EDQ primarily for address verification. Being we are a Geo targeting company, it is very beneficial to use EDQ for a USD data. This helps prevent mis typing or invalid data from coming through. We can also use this feature to provide better quality data by looking at possible lack of data we have through user inputs.

Likelihood to Recommend

Being we are a geo targeting company, one of our largest source of data comes from USD, which can be large firm or simple user interactions. We will these USD data through EDQ and compare the results to what we already have store in our DB. EDQ is extremely helpful in pointing out wrong USD and preventing that data from contaminating our final product.