Data Profiling: The ScribeKey Method
暫譯: 數據剖析：ScribeKey 方法

This practical guide to data profiling will help database professionals and students acquire important skills for data quality, data governance, and metadata projects. Written by a noted expert in the field, Data Profiling will teach you how to capture, explore, and analyze metadata from relational databases, using the free version of ScribeKey’s easy to use command line data profiler.

While data profiling tools share much functionality, one key aspect of ScribeKey’s method makes it a good choice for learning about data profiling; by capturing profiler output as database tables, ScribeKey’s method allows for full integration between metadata and the data it describes. Profiler output describing tables, views, columns, and data values, can be saved in all major databases, including Oracle, SQL Server, DB2, MySql, Postgres, SQLite, and MS Access.

Tabular metadata can also be exported and easily shared as MS Excel, HTML, and XML documents. With no new GUI to learn, you can leverage data exploration tools and techniques that you already possess.

With this flexible tool at your command, Data Profiling offers you an easy and efficient method to learn basic data profiling skills, for describing contents, measuring quality, and tracking change in your databases.

NOTE: Readers not wishing to use ScribeKey's Data Profiler application, but still wanting to learn about data profiling, data quality, and metadata, can still read through the material and learn new concepts by simply studying the profiler output presented in the book and found in the accompanying sample data.