Bernard Marr
Pearson Education
e druk, 2015
9781292081779
Key Business Analytics, Travel Edition
The 60+ tools every manager needs to turn data into insights
Specificaties
Paperback, blz.
|
Engels
Pearson Education |
e druk, 2015
ISBN13: 9781292081779
Rubricering
Juridisch
:
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
A VITAL INSIGHT TO ANALYTICS FOR EVERY BUSINESS
Analytics are essential in any modern business. They help you make better decisions, develop your strategy and identify growth opportunities in business.
Key Business Analytics provides easy access to the most powerful analytics tools. Whether you are a busy manager, business analyst or data professional, you can unlock the insights behind the data and improve your business performance.
Covering over 60 approaches, this jargon-busting book provides a practical overview of analytics tools and explains how to use them. It will help you to understand some of the most valuable analytics techniques, the areas in business to apply them to and how to turn data into insights. From scenario analysis to data mining, learn how to interpret your data and transform the way you make business decisions. It’s the essential guide for every manager.
Specificaties
Inhoudsopgave
<p>Introduction </p> <p>The Raw Material - Data </p> <p>Data Types and Format </p> <p>How to use this book </p> <p> </p> <p>Part One: Bare Analytics </p> <p> </p> <p>1: Business Experiments / Experimental Design / AB testing </p> <p>2: Visual Analytics </p> <p>3: Correlation Analysis </p> <p>4: Scenario Analysis </p> <p>5: Forecasting / Time Series Analysis </p> <p>6: Data mining </p> <p>7: Regression Analysis </p> <p>8: Text Analytics </p> <p>9: Sentiment analysis </p> <p>10: Image Analytics </p> <p>11: Video Analytics </p> <p>12: Voice Analytics </p> <p>13: Monte Carlo Simulation </p> <p>14: Linear Programming </p> <p>15: Cohort Analysis </p> <p>16: Factor analysis </p> <p>17: Neural Network Analysis </p> <p>18: Meta Analytics - Literature Analysis </p> <p> </p> <p>The Part II: Analytics Input Tools or Data Collection Methods </p> <p>19: Quantitative Surveys </p> <p>20: Qualitative Surveys </p> <p>21: Focus Groups </p> <p>22: Interviews </p> <p>23: Ethnography </p> <p>24: Text Capture </p> <p>25: Image Capture</p> <p>26: Sensor Data </p> <p>27: Machine data capture </p> <p> </p> <p>Part Three: Financial Analytics </p> <p>28: Predictive sales analytics </p> <p>29: Customer Profitability analytics </p> <p>30: Product Profitability analytics </p> <p>31: Cashflow analytics </p> <p>32: Value Driver Analytics </p> <p>33: Shareholder value analytics </p> <p>34: Risk Reward Analytics </p> <p>35: Unmet need analytics </p> <p>36: Market Size Analytics </p> <p>37: Demand Forecasting </p> <p>38: Market Trend Analytics </p> <p>39: Non-customer analytics </p> <p>40: Competitor analytics </p> <p>41: Pricing analytics </p> <p>42: Marketing channel analytics </p> <p>43: Brand Analytics </p> <p> </p> <p>Part Five: Customer Analytics</p> <p> </p> <p>44: Customer satisfaction analysis </p> <p>45: Customer Lifetime Value Analytics </p> <p>46: Customer segmentation analytics </p> <p>47: Sales Channel Analytics </p> <p>48: Web Analytics </p> <p>49: Social Media Analytics </p> <p>50: Customer Engagement Analytics </p> <p>51: Customer Churn Analytics </p> <p>52: Customer acquisition analytics </p> <p> </p> <p>Part Six: Employee Analytics </p> <p>53: Capability Analytics </p> <p>54: Capacity Analytics </p> <p>55: Employee Churn Analytics </p> <p>56: Recruitment channel analytics </p> <p>57: Competency acquisition analytics </p> <p>58: Employee Performance Analytics </p> <p>59: Corporate culture analytics </p> <p>60: Leadership Analytics </p> <p> </p> <p>Part Seven: Operational Analytics </p> <p>61: Fraud Detection Analytics </p> <p>62. Core Competency Analytics </p> <p>63: Supply Chain Analytics </p> <p>64: Lean Six Sigma Analytics </p> <p>65. Capacity Utilisation Analytics </p> <p>66: Project and Program Analytics </p> <p>67. Environmental Impact Analytics </p> <p>68: Corporate Social Responsibility (CSR) Analytics </p> <p> </p> <p>Index</p>
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