Big data : evolution, components, challenges and opportunities
Thesis (S.M. in Management of Technology)--Massachusetts Institute of Technology, Sloan School of Management, 2013.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1721.1/80667 |
| _version_ | 1826208279396614144 |
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| author | Zarate Santovena, Alejandro |
| author2 | Michael A. Cusumano. |
| author_facet | Michael A. Cusumano. Zarate Santovena, Alejandro |
| author_sort | Zarate Santovena, Alejandro |
| collection | MIT |
| description | Thesis (S.M. in Management of Technology)--Massachusetts Institute of Technology, Sloan School of Management, 2013. |
| first_indexed | 2024-09-23T14:03:01Z |
| format | Thesis |
| id | mit-1721.1/80667 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T14:03:01Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/806672019-04-12T20:45:32Z Big data : evolution, components, challenges and opportunities Zarate Santovena, Alejandro Michael A. Cusumano. Sloan School of Management. Sloan School of Management. Sloan School of Management. Thesis (S.M. in Management of Technology)--Massachusetts Institute of Technology, Sloan School of Management, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 122-126). This work reviews the evolution and current state of the "Big Data" industry, and to understand the key components, challenges and opportunities of Big Data and analytics face in today business environment, this is analyzed in seven dimensions: Historical Background. The historical evolution and milestones in data management that eventually led to what we know today as Big Data. What is Big Data? Reviews the key concepts around big data, including Volume, Variety, and Velocity, and the key components of successful Big Data initiatives. Data Collection. The most important issue to consider before any big data initiative is to identify the "Business Case" or "Question" we want to answer, no "big data" initiative should be launched without clearly identify the business problem we want to tackle. Data collection strategy has to be closely defined taking in consideration the business case in question. Data Analysis. This section explores the techniques available to create value by aggregate, manipulate, analyze and visualize big data. Including predictive modeling, data mining, and statistical inference models. Data Visualization. Visualization of data is one of the most powerful and appealing techniques for data exploration. This section explores the main techniques for data visualization so that the characteristics of the data and the relationships among data items can be reported and analyzed. Impact. This section explores the potential impact and implications of big data in value creation in five domains: Insurance, Healthcare, Politics, Education and Marketing. Human Capital. This chapter explores the way big data will influence business processes and human capital, explore the role of the "Data Scientist" and analyze a potential shortage of data experts in coming years. Infrastructure and Solutions. This chapter explores the current professional services and infrastructure offering and how this industry and makes a review of vendors available in different specialties around big data. by Alejandro Zarate Santovena. S.M.in Management of Technology 2013-09-12T19:18:06Z 2013-09-12T19:18:06Z 2013 2013 Thesis http://hdl.handle.net/1721.1/80667 857767881 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 126 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Sloan School of Management. Zarate Santovena, Alejandro Big data : evolution, components, challenges and opportunities |
| title | Big data : evolution, components, challenges and opportunities |
| title_full | Big data : evolution, components, challenges and opportunities |
| title_fullStr | Big data : evolution, components, challenges and opportunities |
| title_full_unstemmed | Big data : evolution, components, challenges and opportunities |
| title_short | Big data : evolution, components, challenges and opportunities |
| title_sort | big data evolution components challenges and opportunities |
| topic | Sloan School of Management. |
| url | http://hdl.handle.net/1721.1/80667 |
| work_keys_str_mv | AT zaratesantovenaalejandro bigdataevolutioncomponentschallengesandopportunities |