| Judul | Data Analytics for Business / Ira J. Haimowitz |
| Pengarang | Haimowitz, Ira J. |
| Penerbitan | New York : Routledge, 2022 |
| Deskripsi Fisik | 178 p. :ilus |
| ISBN | 9780429300363 |
| Subjek | COMPUTER SCIENCE, ECONOMICS, FINANCE, BUSINESS & INDUSTRY |
| Catatan | Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications. The foundation of this text is the author’s 20-plus years of developing and delivering big data and artificial intelligence solutions across multiple industries: financial services, pharmaceuticals, consumer packaged goods, media, and retail. He provides guidelines and summarized cases for those studying or working in the fields of data science, data engineering, and business analytics. The book also offers a distinctive style: a series of essays, each of which summarizes a critical lesson or provides a step-by-step business process, with specific examples of successes and failures. Sales and marketing executives, project managers, business and engineering professionals, and graduate students will find this clear and compr |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
https://www.taylorfrancis.com/books/mono/10.4324/9780429300363 |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 010123292 | 650.028 5 Hai d | Baca Online | Perpustakaan Pusat - Online Resources Ebook |
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| 500 | # | # | $a Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications. The foundation of this text is the author’s 20-plus years of developing and delivering big data and artificial intelligence solutions across multiple industries: financial services, pharmaceuticals, consumer packaged goods, media, and retail. He provides guidelines and summarized cases for those studying or working in the fields of data science, data engineering, and business analytics. The book also offers a distinctive style: a series of essays, each of which summarizes a critical lesson or provides a step-by-step business process, with specific examples of successes and failures. Sales and marketing executives, project managers, business and engineering professionals, and graduate students will find this clear and comprehensive book the ideal companion when navigating the complex world of big data analytics. |
| 650 | # | # | $a COMPUTER SCIENCE, ECONOMICS, FINANCE, BUSINESS & INDUSTRY |
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