Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help
What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is.
Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects.
Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book.
Data Science For Dummies demonstrates:
The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise
Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.
By:
Lillian Pierson (Data-Mania)
Imprint: For Dummies
Country of Publication: United States
Edition: 3rd edition
Dimensions:
Height: 234mm,
Width: 185mm,
Spine: 31mm
Weight: 590g
ISBN: 9781119811558
ISBN 10: 1119811554
Pages: 432
Publication Date: 01 September 2021
Audience:
General/trade
,
ELT Advanced
Format: Paperback
Publisher's Status: Active
Introduction 1 Part 1: Getting Started with Data Science 5 Chapter 1: Wrapping Your Head Around Data Science 7 Chapter 2: Tapping into Critical Aspects of Data Engineering 19 Part 2: Using Data Science to Extract Meaning from Your Data 37 Chapter 3: Machine Learning Means Using a Machine to Learn from Data 39 Chapter 4: Math, Probability, and Statistical Modeling 51 Chapter 5: Grouping Your Way into Accurate Predictions 77 Chapter 6: Coding Up Data Insights and Decision Engines 103 Chapter 7: Generating Insights with Software Applications 137 Chapter 8: Telling Powerful Stories with Data 161 Part 3: Taking Stock of Your Data Science Capabilities 187 Chapter 9: Developing Your Business Acumen 189 Chapter 10: Improving Operations 205 Chapter 11: Making Marketing Improvements 229 Chapter 12: Enabling Improved Decision-Making 245 Chapter 13: Decreasing Lending Risk and Fighting Financial Crimes 265 Chapter 14: Monetizing Data and Data Science Expertise 275 Part 4: Assessing Your Data Science Options 289 Chapter 15: Gathering Important Information about Your Company 291 Chapter 16: Narrowing In on the Optimal Data Science Use Case 311 Chapter 17: Planning for Future Data Science Project Success 327 Chapter 18: Blazing a Path to Data Science Career Success 341 Part 5: The Part of Tens 367 Chapter 19: Ten Phenomenal Resources for Open Data 369 Chapter 20: Ten Free or Low-Cost Data Science Tools and Applications 381 Index 397
Lillian Pierson is the CEO of Data-Mania, where she supports data professionals in transforming into world-class leaders and entrepreneurs. She has trained well over one million individuals on the topics of AI and data science. Lillian has assisted global leaders in IT, government, media organizations, and nonprofits.
