EBK USING MIS
10th Edition
ISBN: 8220103633642
Author: KROENKE
Publisher: YUZU
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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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Chapter 9 Solutions
EBK USING MIS
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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- What impact does the Extract, Transform, and Load (ETL) process have on a Data Warehouse's performance? What are some of the data sources that will be used in this process, and what are some of the challenges that the many data sources will present? What impact does the ETL technique have on the quality of the data warehouse?arrow_forwardHow does data transformation contribute to the effectiveness of a data warehouse, and what are some common techniques employed for data transformation?arrow_forwardExplain the concept of data marts and their relationship to a data warehouse. What are the advantages and disadvantages of using data marts for specific business units or departments?arrow_forward
- A) Explain why data quality problems can become obstacles in a company with a long history is it is going to implement a data warehouse? List 5 example? B) explain briefly how their impacts can he reduced? (Hints: problems might be at the data pre-processing stage)arrow_forwardDescribe the concept of "data mart" in data warehousing. What is the purpose of creating data marts, and how do they relate to the central data warehouse?arrow_forwardData quality in data warehouses—what do you think? What are the benefits and suggestions for utilizing excellent data?arrow_forward
- How do data warehouses handle data transformation and cleansing to ensure data quality and consistency?arrow_forwardHow do data warehouses handle data integration from various sources, and what methods are used for data cleansing and transformation?arrow_forwardHow does data warehousing support data governance and compliance with regulations such as GDPR and HIPAA?arrow_forward
- Explain the concept of data mart within a data warehousing environment. How does it differ from a data warehouse, and what are the specific use cases where data marts play a crucial role in business intelligence?arrow_forwardWho has challenges and experiences discomfort as a result of depending on distinct data silos, and how does this occur?arrow_forwardExplain the ETL (Extract, Transform, Load) process in data warehousing. What are its key steps, and why is it crucial for maintaining data quality?arrow_forward
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