
Using MIS (10th Edition)
10th Edition
ISBN: 9780134606996
Author: David M. Kroenke, Randall J. Boyle
Publisher: PEARSON
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Chapter 9.9, Problem 9.3ARQ
Explanation of Solution
Need and functions of data warehouses:
Data warehouse:
A data warehouse is an architecture that is used to gather and collect all the non-volatile, subject oriented, and integrated data, by which the analysts in an organization can study and take informed decisions.
Data mart:
In order to address a particular functional or business area, a small part of data warehouse is used, which is called data mart.
- Data marts contain only functionally related data, and they get their data from data warehouses.
Need for data warehouse and data marts:
- There is a concern for security and control to use operational data by analysts.
- Operational data is not suited for business intelligence (BI) analysis, as there will be reduced system performance. This is because the BI analysis requires considerable processing.
- Due to these reasons, most organizations extract operational data, and in order to manage the organizations data, data warehouse is required.
Functions of data warehouse and data marts:
- Obtain and integrate all the incoming data from various data sources.
- Gather all the data and cleanse them by finding out the errors and correcting them.
- Transform the cleaned data into warehouse format, organize, and relate those using data transformation techniques.
- Categorize the data by sorting, summarizing, and building indices and partition for the data present in the data warehouse.
Role of data warehouse components:
- Data cleaning and data extraction tools:
- First, the data from operational databases and other internal and external data are extracted and are cleaned using data cleaning tools. And then, the data are prepared for BI Processing.
- Data warehouse’s
database management system (DBMS): - The data that are prepared for BI Processing are stored in a data warehouse.
- The data warehouse’s database management system contains the data from data warehouse metadata and data warehouse database.
- Business intelligence tools:
- The business intelligence users are usually specialists in data analysis, who use business intelligence tools on the data stored on the data warehouse.
Problems in the data used for data mining and sophisticated reporting:
Curse of dimensionality:
- The curse of dimensionality is refers to the problem that arises when one analyses and organizes the data in high-dimensional spaces...
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8.4 Self-Bias Configuration
20. Determine Zi. Zo. and A,, for the network of Fig. 8.73 if gf, = 3000 μS and gos = 50 μs.
21. Determine Z, Zo, and A, for the network of Fig. 8.73 if the 20-uF capacitor is removed and the
parameters of the network are the same as in Problem 20. Compare results with those of
Problem 20.
+12 V
3.3 ΚΩ
HE
C₂
Vo
Z
Zo
C₁
10 ΜΩ
Z₁
1.1 ΚΩ
Cs 20 µF
FIG. 8.73
Problems 20, 21, 22, and 59.
21. Determine Zi, Zo, and A, for the network of Fig. 8.73 if the 20-μF capacitor is removed and the
parameters of the network are the same as in Problem 20. Compare results with those of
Problem 20.
+12 V
3.3 ΚΩ
+6
C₂
C₁
Z₁
10 ΜΩ
1.1 ΚΩ
Cs
20 μF
FIG. 8.73
Zo
Chapter 9 Solutions
Using MIS (10th Edition)
Ch. 9.3 - Prob. 1EGDQCh. 9.3 - Prob. 2EGDQCh. 9.3 - Prob. 3EGDQCh. 9.3 - Prob. 4EGDQCh. 9.6 - Prob. 1BFSQCh. 9.6 - Prob. 2BFSQCh. 9.6 - Prob. 3BFSQCh. 9.6 - Prob. 4BFSQCh. 9.9 - Prob. 1SGDQCh. 9.9 - Prob. 2SGDQ
Ch. 9.9 - Prob. 3SGDQCh. 9.9 - Prob. 4SGDQCh. 9.9 - Prob. 5SGDQCh. 9.9 - Prob. 9.1ARQCh. 9.9 - Prob. 9.2ARQCh. 9.9 - Prob. 9.3ARQCh. 9.9 - Prob. 9.4ARQCh. 9.9 - Prob. 9.5ARQCh. 9.9 - Prob. 9.6ARQCh. 9.9 - Prob. 9.8ARQCh. 9.9 - Prob. 9.9ARQCh. 9 - Prob. 9.1UYKCh. 9 - Prob. 9.2UYKCh. 9 - Prob. 9.3UYKCh. 9 - Prob. 9.4UYKCh. 9 - Prob. 9.5UYKCh. 9 - Prob. 9.6UYKCh. 9 - Prob. 9.7UYKCh. 9 - Prob. 9.8UYKCh. 9 - Prob. 9.9CE9Ch. 9 - Prob. 9.1CE9Ch. 9 - Prob. 9.11CE9Ch. 9 - Prob. 9.12CE9Ch. 9 - Prob. 9.13CE9Ch. 9 - Prob. 9.14CE9Ch. 9 - Prob. 9.15CE9Ch. 9 - Prob. 9.16CS9Ch. 9 - Prob. 9.17CS9Ch. 9 - Prob. 9.18CS9Ch. 9 - Prob. 9.19CS9Ch. 9 - Prob. 9.22MML
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