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Data Profiling in Cloud Migration: Data Quality Measures While Migrating Data from a Data Warehouse to the Google Cloud Platform.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data Profiling in Cloud Migration: Data Quality Measures While Migrating Data from a Data Warehouse to the Google Cloud Platform./
作者:	Cabral, Andreia Filipa Goncalves.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	65 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-03, Section: A.
Contained By:	Dissertations Abstracts International83-03A.
標題:	Metadata. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28727298
ISBN:	9798544214847

Data Profiling in Cloud Migration: Data Quality Measures While Migrating Data from a Data Warehouse to the Google Cloud Platform.
Cabral, Andreia Filipa Goncalves.

Data Profiling in Cloud Migration: Data Quality Measures While Migrating Data from a Data Warehouse to the Google Cloud Platform. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 65 p.

Source: Dissertations Abstracts International, Volume: 83-03, Section: A.

Thesis (Master's)--Universidade NOVA de Lisboa (Portugal), 2021.

This item must not be sold to any third party vendors.

In today times, corporations have gained a vast interest in data. More and more, companies realized that the key to improving their efficiency and effectiveness and understanding their customers' needs and preferences better was reachable by mining data. However, as the amount of data grow, so must the companies necessities for storage capacity and ensuring data quality for more accurate insights. As such, new data storage methods must be considered, evolving from old ones, still keeping data integrity. Migrating a company's data from an old method like a Data Warehouse to a new one, Google Cloud Platform is an elaborate task. Even more so when data quality needs to be assured and sensible data, like Personal Identifiable Information, needs to be anonymized in a Cloud computing environment. To ensure these points, profiling data, before or after it migrated, has a significant value by design a profile for the data available in each data source (e.g., Databases, files, and others) based on statistics, metadata information, and pattern rules. Thus, ensuring data quality is within reasonable standards through statistics metrics, and all Personal Identifiable Information is identified and anonymized accordingly. This work will reflect the required process of how profiling Data Warehouse data can improve data quality to better migrate to the Cloud.

ISBN: 9798544214847Subjects--Topical Terms:

590006
Metadata.

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