Three-Dimensional Analysis - Data Profiling Techniques
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Three-Dimensional Analysis - Data Profiling Techniques
Data Profiling is a relatively new concept in understanding your data. It was originally introduced to the market by Evoke Software in the late 90 s. Since then a number of vendors have introduced data profiling software. However, none of the vendors spends much time explaining the techniques of using the software to profile the data. Most of their efforts are more like here is what the software does; now you figure out how to use it to understand your data better. The purpose of this book would be to turn the situation around. You have data, what techniques would you use to get the most information using a profiling tool or some other method. A simple example is a date field. There are a number of techniques you can use to test for anomalies in a date field. These would help you validate or invalidate the information contained in that field. While the book is geared toward using a profiling tool to understand, many of the techniques included in the book do not explicitly require one. Approach: The book is based upon years of practical experience in the field, profiling data for many companies. It uses real world examples throughout the book. It can be a starter book for someone who is just starting to profile data and as a reference for when they come across an industry type of data they have not encountered yet The book starts out at a very general level in the discussion of profiling and then slowly gets more and more detailed into specific techniques. After reading this book, everyone will get a bigger benefit from the software their company purchased to accelerate their data related project. This book should be required reading for anyone involved in a data quality, data integration, or data migration project. The author has given numerous seminars on data profiling techniques. Target readership: There are at least six target audiences for this book. - Business User/Analyst - any business user who wants to understand the underlying data quality better for their business unit s needs. - Database Administrator (DBA) Database administrators that need to explore the data quality and structure of the databases they administer. - ETL (Extract, Transform, and Load) Developer ETL developers that want to get clear specifications for their development needs. - Profiling Facilitator / Project Manager Members of the team that have been trained and are expected to run the profiling software or are running a data related project that will include profiling the data. - Data Steward Like business users, data stewards also need to get a better understanding of the data for which they are responsible. - Data Modeler Modelers that want to understand and verify the structure of their systems. Each of these different team members would benefit from reading and using the knowledge gained from it.