JD:
Improve the ability to search data by tagging it with keywords, descriptions, or assigning it to a category
Assess data quality, including whether the data conforms to particular standards or patterns
Discover metadata of the source database, including value patterns and distributions, key candidates, foreign-key candidates, and functional dependencies
Assess whether known metadata accurately describes the actual values in the source database
Understanding data challenges early in any data intensive project, so that late project surprises are avoided. Finding data problems late in the project can lead to delays and cost overruns.
Have an enterprise view of all data, for uses such as master data management, where key data is needed, or data governance for improving data quality.
Expertise in Oracle PL/SQL
Thanks & Regards,
Nagesh Bade
4229 Lafayette Center Dr., Suite #1625, Chantilly, VA 20151
Tel: 703-831-8282 Ext. 202, Direct: 213-262-5570
Email: nagesh@canopyone.com Web: www.canopyone.com
LinkedIn: www.linkedin.com/in/nageshbade
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