Oracle Data Quality for Data Integration and Oracle Data Profiling 11g
By Julien Testut-Oracle on Oct 07, 2010
In this post we'll have a look at Oracle Data Quality for Data Integrator (ODQ) and Oracle Data Profiling (ODP) 11g which have been recently released along with Oracle Data Integrator (ODI) 11g. Those 2 new components of the Oracle Data Integration Solutions offering extend the data quality capabilities of ODI.
Oracle Data Profiling allows users to discover and investigate the content and the structure of their different data sources, it also gives users the ability to monitor the evolution of data quality over time using Time Series.
Oracle Data Quality for Data Integrator helps companies standardize, validate, cleanse and enrich their data. Using out-of-the-box rules ODQ can, for example, cleanse customer names as well as validate and enrich their addresses. Oracle Data Quality for Data Integrator provides rules and libraries for many different countries around the world and can be used for any data domains.
What's New in Oracle Data Quality for Data Integrator and Oracle Data Profiling 11g
The 11g releases of ODQ and ODP introduce many new features and improvements including:
- Core enhancements to the platform: performance, availability, security and management
- Reusable business rules library
- Enhanced International Support
- Improved address verification
- Better support for product, materials, suppliers and financial data domains
Enhancements have also been made on their integration with Oracle Data Integrator, both ODQ and ODP provide metadata exchange capabilities with ODI and ODQ jobs can be easily included within ODI workflows.
When should I use Oracle Data Profiling and Oracle Data Quality for Data Integrator?
Both products can be used to complement any data integration projects, having a pervasive and continuous data quality process in place is critical for an organization. Data quality issues can be extremely costly if not taken into account early on as it can pollute the systems relying on the data like your Business Intelligence applications and it may delay the delivery of your data integration projects.
So how does it work?: usually you start by profiling your different data sources before you integrate them together. Oracle Data Profiling can help you uncover what you don't know about your data by identifying any data defects as well as the relationships between your data sources. This can help your company save both time and money.
Once you have identified the problems you may find that some of them can be fixed at the Oracle Data Integrator level while others like de-duplicating your product or customer data, matching records together using complex algorithms, applying cleansing rules or enriching addresses are best implemented using Oracle Data Quality for Data Integrator.
When your data quality processes are designed and deployed you can orchestrate the end to end data integration process using Oracle Data Integrator by adding your ODQ jobs inside ODI workflows.
Finally once the cleansing phase is over you need to keep on monitoring your different data sources using the Oracle Data Profiling Time Series feature to ensure your data quality process is continuous.
To learn more about Oracle Data Quality for Data Integrator 11g and Oracle Data Profiling 11g please have a look at the following resources:
- Oracle Data Quality for Data Integrator and Oracle Data Profiling page on OTN
- Oracle Data Quality for Data Integrator and Oracle Data Profiling Data Sheet