Pearson eText for Modern Database Management -- Instant Access (Pearson+)
13th Edition
ISBN: 9780137305940
Author: Jeffrey Hoffer, Ramesh Venkataraman
Publisher: PEARSON+
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Chapter 9, Problem 9.30RQ
Program Plan Intro
Five steps in data reconciliation process.
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Chapter 9 Solutions
Pearson eText for Modern Database Management -- Instant Access (Pearson+)
Ch. 9 - Prob. 9.1RQCh. 9 - Prob. 9.2RQCh. 9 - Prob. 9.3RQCh. 9 - List the five major trends that necessitate data...Ch. 9 - Prob. 9.5RQCh. 9 - Prob. 9.6RQCh. 9 - Prob. 9.7RQCh. 9 - Prob. 9.8RQCh. 9 - Prob. 9.9RQCh. 9 - Prob. 9.10RQ
Ch. 9 - List four objectives of derived data.Ch. 9 - Prob. 9.12RQCh. 9 - Prob. 9.13RQCh. 9 - Explain the pros and cons of logical data marts.Ch. 9 - Prob. 9.15RQCh. 9 - What is a helper table, and why is it often used...Ch. 9 - Describe the characteristics of a surrogate key as...Ch. 9 - Prob. 9.18RQCh. 9 - What is the purpose of conformed dimensions for...Ch. 9 - Prob. 9.20RQCh. 9 - Prob. 9.21RQCh. 9 - Prob. 9.22RQCh. 9 - Prob. 9.23RQCh. 9 - Prob. 9.24RQCh. 9 - Prob. 9.25RQCh. 9 - Describe the current key trends in data...Ch. 9 - Discuss the benefits of offering data warehousing...Ch. 9 - Prob. 9.28RQCh. 9 - List six typical characteristics of reconciled...Ch. 9 - Prob. 9.30RQCh. 9 - Prob. 9.31RQCh. 9 - Prob. 9.32RQCh. 9 - Prob. 9.33RQCh. 9 - Describe some field-level and record-level data...Ch. 9 - Prob. 9.35PAECh. 9 - Prob. 9.36PAECh. 9 - Prob. 9.37PAECh. 9 - Prob. 9.38PAECh. 9 - You are to construct a star schema for Simplified...Ch. 9 - Simplified Automobile Insurance Company would like...Ch. 9 - Prob. 9.41PAECh. 9 - Prob. 9.42PAECh. 9 - Prob. 9.43PAECh. 9 - Prob. 9.45PAECh. 9 - Prob. 9.46PAECh. 9 - Prob. 9.47PAECh. 9 - Prob. 9.48PAECh. 9 - Prob. 9.49PAECh. 9 - Prob. 9.50PAECh. 9 - Prob. 9.51PAECh. 9 - Prob. 9.52PAECh. 9 - Prob. 9.53PAECh. 9 - Prob. 9.54PAE
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- Discuss the problems that can be caused by data redundancy.arrow_forwardExplain how the data reconciliation process is affected by the term "extract–transform–load."arrow_forwardWhat are the three most common kinds of data anomalies that result from data redundancy? What steps can be taken to ensure that something like this does not occur?arrow_forward
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