DATA SCIENCE AND DATA ANALYTICS : (Record no. 72146)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03842cam a2200493Ki 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9781003111290 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220711212801.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 211007s2021 xx ob 0|1 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781003111290 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1003111297 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781000423198 |
| -- | (electronic bk. : PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1000423190 |
| -- | (electronic bk. : PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781000423228 |
| -- | (electronic bk. : EPUB) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1000423220 |
| -- | (electronic bk. : EPUB) |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 005.7 |
| 245 00 - TITLE STATEMENT | |
| Title | DATA SCIENCE AND DATA ANALYTICS : |
| Sub Title | opportunities and challenges. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (1 volume) : |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm's productivity. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Tyagi, Amit Kumar, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.taylorfrancis.com/books/9781003111290 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | [Place of publication not identified] : |
| -- | CHAPMAN & HALL CRC, |
| -- | 2021. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 588 ## - | |
| -- | OCLC-licensed vendor bibliographic record. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | COMPUTERS / Database Management / Data Mining |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | COMPUTERS / Database Management / General |
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