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Titel: Three-Dimensional Analysis - Data Profiling ...
Verlag: Data Profiling LLC
Einband: Soft cover
Brand New, Unread Copy in Perfect Condition. A+ Customer Service!. Buchnummer des Verkäufers ABE_book_new_0980083303
Inhaltsangabe: 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.
Über den Autor: Ed Lindsey has a BBA in math and information technology and an MBA in Management and Information Technology from Pace University. His career in information technology spans more than 30 years. He has worked on mainframes, mini-computers, and PCs and has done extensive work in voice and data networks. He has certifications with both Microsoft and Cisco. His more recent accomplishments include designing high availability transaction processing systems while working at AT&T Bell Laboratories. He moved from the Labs to NCR Teradata where he was involved with building data warehouses for the communication industry. The data warehouse experience showed him the need for improving data quality. He became involved with data quality in the 90 s, becoming a trailblazer and preaching the need to profile data as part of any data related project. Ed has worked at Evoke, Ascential, IBM, Similarity Systems, and Informatica. He has worked with different profiling products including: DataFlux dfPower Studio, ProfileStage, Axio, and Informatica Data Explorer. Ed has a wealth of experience working with a variety of companies, in different industries helping them to identify and fix data quality issues.
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