| 000 | 02019nam a22002897i 4500 | ||
|---|---|---|---|
| 005 | 20250807160818.0 | ||
| 008 | 250807s2024 us a|||fr|||| 001 0 eng d | ||
| 020 | _a9781266931628 | ||
| 040 |
_aEG-GaU _cEG-GaU _dEG-GaU _erda |
||
| 082 | 0 | 4 |
_223 _a658.8 _bj.h.e. |
| 100 | 1 |
_aHair, Joseph F., _eauthor. _961703 |
|
| 245 | 1 | 0 |
_aEssentials of marketing analytics : _b2024 Release ISE / _cJoseph F. Hair, Dana E. Harrison, Haya Ajjan. |
| 250 | _aFirst edition. | ||
| 264 | 1 |
_aNew York : _bMcGraw Hill Education, _c2024. |
|
| 300 |
_a474 pages : _billustrations? ; _c25 cm. |
||
| 336 |
_2rdacontent _atext _btxt |
||
| 337 |
_2rdamedia _aunmediated _bn |
||
| 338 |
_2rdacarrier _avolume _bnc |
||
| 505 | _aPart 1: Overview of marketing analytics and data management – 1. Introduction to marketing analytics; 2. Data management -- Part 2: Exploring and visualizing data patterns – 3. Exploratory data analysis using cognitive analytics; 4. Data visualization -- Part 3: Analytical methods for supervised learning – 5. Regression analysis; 6. Neural networks; 7. Automated machine learning -- Part 4: Analytical methods for unsupervised learning – 8. Cluster analysis; 9. Market basket analysis -- Part 5: Emerging analytical approaches – 10. Natural language processing; 11. Social network analysis; 12. Fundamentals of digital marketing analytics. | ||
| 520 | _aA timely, comprehensive introduction to marketing analytics for undergraduate and graduate business students. Combines theory with tools like Tableau and Python and explores topics such as neural networks, social network analysis, automated machine learning, and NLP. Supported by McGraw Hill Connect digital platform.turn0search6turn0search2turn0search7 | ||
| 650 |
_aMarketing analytics. _961704 |
||
| 650 |
_aData visualization. _960465 |
||
| 700 | 1 |
_aHarrison, Dana E., _eauthor. _961705 |
|
| 700 | 1 |
_aAjjan, Haya, _eauthor. _961706 |
|
| 942 |
_2ddc _cBK |
||
| 999 |
_c11558 _d11558 |
||