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Modeling Data Analytics Capabilities...

Bonilla, JeanCarlo (J.C).

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Modeling Data Analytics Capabilities from Text: An Explanatory Analysis on Data Mining Initiatives.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Data Analytics Capabilities from Text: An Explanatory Analysis on Data Mining Initiatives./
作者:	Bonilla, JeanCarlo (J.C).
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	160 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
Contained By:	Dissertation Abstracts International78-10A(E).
標題:	Information science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10254162
ISBN:	9781369835144

Modeling Data Analytics Capabilities from Text: An Explanatory Analysis on Data Mining Initiatives.
Bonilla, JeanCarlo (J.C).

Modeling Data Analytics Capabilities from Text: An Explanatory Analysis on Data Mining Initiatives. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 160 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.

Thesis (Ph.D.)--Polytechnic Institute of New York University, 2017.

Fueled by the promise of data mining and analytics, a promise of changing the competitive landscape by providing, competitive advantage, business efficiency, and ultimately, a better bottom-line, organizations have quickly resourced analytics initiatives. At the same time, academic research agendas continue to grow in interest and publications around the data analytics revolution. However, the emphasis of the research and practice have focused on the technology and methods behind the informatics world needed to manage data across platforms, the size, structure, and security of data, and off course the proliferations of advanced modelling for extracting meaning from raw data or predicting outcomes. As such, this research focuses on understanding the environment around data analytics and informatics, particularly around the implications of transforming information into insight and then actions. Specifically, this study deals with the organizational requirements to move from intuition-based management to data-driven management, how firms organize along and align resources for analytics readiness, and to decode the trajectories taken by firms as advance in data analytics maturity.

ISBN: 9781369835144Subjects--Topical Terms:

554358
Information science.

Modeling Data Analytics Capabilities from Text: An Explanatory Analysis on Data Mining Initiatives.
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520 $a Fueled by the promise of data mining and analytics, a promise of changing the competitive landscape by providing, competitive advantage, business efficiency, and ultimately, a better bottom-line, organizations have quickly resourced analytics initiatives. At the same time, academic research agendas continue to grow in interest and publications around the data analytics revolution. However, the emphasis of the research and practice have focused on the technology and methods behind the informatics world needed to manage data across platforms, the size, structure, and security of data, and off course the proliferations of advanced modelling for extracting meaning from raw data or predicting outcomes. As such, this research focuses on understanding the environment around data analytics and informatics, particularly around the implications of transforming information into insight and then actions. Specifically, this study deals with the organizational requirements to move from intuition-based management to data-driven management, how firms organize along and align resources for analytics readiness, and to decode the trajectories taken by firms as advance in data analytics maturity.
520 $a Grounded in the resourced-based view of firm, this study uses a corpus of over 2352 business articles documenting analytics initiatives as a way to explore, decode, and understand firms in their quest to develop analytics capabilities over time. Using machine learning text mining to automatically detect analytics-based resources and interpretative methods to assets the context of the initiatives, this study found a total of 273 analytics-based resources, 6 unique data analytics capabilities, and 9 recurrent trajectories that mediate successful analytics implementations across enterprises. In terms of contributions, this research proposes the emergence of analytics-based resources and precursors of data analytics capabilities. It also posits that a distinctive type of capability is required to transition from intuition-based management to data-driven management and that this data analytics capability influences organizations' culture, management, strategy, and operations. In addition, this study developed a robust and scalable methodology for interpretation and analysis of large volume texts.
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