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Advanced Analytics and Data Science a Complete Guide

Advanced Analytics and Data Science a Complete Guide
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 288
Release: 2018-08-24
Genre:
ISBN: 9780655345152
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Risk factors: what are the characteristics of Advanced Analytics and Data Science that make it risky? Why is it important to have senior management support for a Advanced Analytics and Data Science project? What will drive Advanced Analytics and Data Science change? Is there a Advanced Analytics and Data Science Communication plan covering who needs to get what information when? Does Advanced Analytics and Data Science systematically track and analyze outcomes for accountability and quality improvement? This extraordinary Advanced Analytics and Data Science self-assessment will make you the credible Advanced Analytics and Data Science domain authority by revealing just what you need to know to be fluent and ready for any Advanced Analytics and Data Science challenge. How do I reduce the effort in the Advanced Analytics and Data Science work to be done to get problems solved? How can I ensure that plans of action include every Advanced Analytics and Data Science task and that every Advanced Analytics and Data Science outcome is in place? How will I save time investigating strategic and tactical options and ensuring Advanced Analytics and Data Science costs are low? How can I deliver tailored Advanced Analytics and Data Science advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Advanced Analytics and Data Science essentials are covered, from every angle: the Advanced Analytics and Data Science self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Advanced Analytics and Data Science outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Advanced Analytics and Data Science practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Advanced Analytics and Data Science are maximized with professional results. Your purchase includes access details to the Advanced Analytics and Data Science self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Data Science and Advanced Analytics a Complete Guide

Data Science and Advanced Analytics a Complete Guide
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 288
Release: 2018-10-18
Genre:
ISBN: 9780655434245
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How do senior leaders actions reflect a commitment to the organizations Data Science and Advanced Analytics values? What other organizational variables, such as reward systems or communication systems, affect the performance of this Data Science and Advanced Analytics process? How can you incorporate support to ensure safe and effective use of Data Science and Advanced Analytics into the services that you provide? Does Data Science and Advanced Analytics analysis show the relationships among important Data Science and Advanced Analytics factors? What are the essentials of internal Data Science and Advanced Analytics management? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Science and Advanced Analytics investments work better. This Data Science and Advanced Analytics All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data Science and Advanced Analytics Self-Assessment. Featuring 668 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Science and Advanced Analytics improvements can be made. In using the questions you will be better able to: - diagnose Data Science and Advanced Analytics projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data Science and Advanced Analytics and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data Science and Advanced Analytics Scorecard, you will develop a clear picture of which Data Science and Advanced Analytics areas need attention. Your purchase includes access details to the Data Science and Advanced Analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Data Science for Marketing Analytics

Data Science for Marketing Analytics
Author: Mirza Rahim Baig
Publisher: Packt Publishing Ltd
Total Pages: 637
Release: 2021-09-07
Genre: Computers
ISBN: 1800563884
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Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

Leading with AI and Analytics: Build Your Data Science IQ to Drive Business Value

Leading with AI and Analytics: Build Your Data Science IQ to Drive Business Value
Author: Eric Anderson
Publisher: McGraw Hill Professional
Total Pages: 353
Release: 2020-11-23
Genre: Business & Economics
ISBN: 1260459152
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Lead your organization to become evidence-driven Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.

Data Science

Data Science
Author: Richard Hurley
Publisher:
Total Pages: 182
Release: 2020-01-19
Genre: Computers
ISBN: 9781952191237
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This book will discuss everything that you need to know when it comes to working in the field of data science. This world has changed, and with the modern technology that we have, it is easier than ever for companies to amass a large amount of data on the industry, on their competition, on their products, and their customers.

Advanced Data Science and Analytics with Python

Advanced Data Science and Analytics with Python
Author: Jesus Rogel-Salazar
Publisher: CRC Press
Total Pages: 424
Release: 2020-05-05
Genre: Business & Economics
ISBN: 0429822324
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Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences – in this case, literally to the users’ fingertips in the form of an iPhone app. About the Author Dr. Jesús Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.

Advanced Analytics Methodologies

Advanced Analytics Methodologies
Author: Michele Chambers
Publisher: Pearson Education
Total Pages: 337
Release: 2015
Genre: Business & Economics
ISBN: 0133498603
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Advanced Analytics Methodologies is today's definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its expanded, cutting-edge coverage helps readers systematically "jump the gap" between their organization's current analytical capabilities and where they need to be. Step by step, Michele Chambers and Thomas Dinsmore help readers customize a complete roadmap for implementing analytics that supports unique corporate strategies, aligns with specific corporate cultures, and serves unique customer and stakeholder communities. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore provide advanced applications and examples not available elsewhere, describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. They show how to: Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and many line-of-business executives.

No-Code Data Science

No-Code Data Science
Author: David Patrishkoff
Publisher:
Total Pages: 0
Release: 2023-10-16
Genre: Computers
ISBN: 9781312040403
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No Code Data Science is a revolutionary book that democratizes the application of predictive analytics for organizations of all sizes. This first-of-its-kind textbook book is designed to empower readers with the ability to leverage advanced analytics, machine learning, and AI without using a programming language, such as Python or R.It's a comprehensive guide to no-code data science (NCDS) that applies free, no-code, and open-source software with Orange visual programming software, JASP, and BlueSky Statistics. A no-shortcuts approach to ML and AI is applied to maximize the accuracy and application potential of predictive models. The NCDS approach is akin to constructing predictive models with pre-made LEGO bricks (visual programming) versus tediously molding shapes from clay (manual coding). A practical how-to approach to predictive modeling is offered while insisting on the rigor of our disciplined NCDS process. Hands-on data exercises are included in the first eleven chapters. QR code links to educational videos are included in most chapters.Data science background is first explored, discussing basic definitions and data scientist skill sets. This is followed by chapters on data preparation, wrangling, and data visualization. Predictive analytics is covered in chapters on machine learning models and model evaluation. Both supervised and unsupervised learning are included in the discourse. Time series forecasting, survival analysis, and geolocation are covered in separate chapters. Artificial intelligence is featured in chapters on image analysis and text mining. Lastly, the potential impact of machine learning and artificial intelligence on Industry 4.0 is covered in the last chapter. A pathway for statisticians, Lean Six Sigma practitioners, and other professionals is offered to learn predictive modeling techniques to enable organizations to successfully pursue Industry 4.0 goals.

Data Science

Data Science
Author: Herbert Jones
Publisher:
Total Pages: 134
Release: 2020-01-03
Genre: Computers
ISBN: 9781647483043
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2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying

A Complete Guide to Data Science Essentials

A Complete Guide to Data Science Essentials
Author: Miguel
Publisher:
Total Pages: 0
Release: 2023-11-09
Genre:
ISBN: 9789358684995
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Explore the vast field of data science with "A Complete Guide to Data Science Essentials," an easy-to-use guide that breaks down the complicated parts of this ever-changing field. This book, written by Miguel, a seasoned data science expert, takes you step-by-step through the most important ideas, methods, and tools that will shape the data-driven world in 2023. Learn about important things like machine learning, statistical analysis, and computer languages (like Python, R, etc.) to get the skills you need to work in the ever-changing field of data science. Learn the mathematical ideas that support data science to build a strong base for advanced analytics and fixing problems. Stay ahead of the curve by learning how to use popular computer languages to do cutting edge data manipulation, analysis, and visualization. The book puts a lot of stress on practical scripting and coding, making sure that readers learn how to turn raw data into insights that they can use. Master the art of cleaning and preparing data to make it more reliable and of higher quality. Learn the newest ways to collect and source data. With an emphasis on real-world uses, the guide talks about the problems that come up when you have to deal with missing values and outliers and gives you useful ways to make your data analysis stronger. "A Complete Guide to Data Science Essentials" is the book you need whether you're an experienced data professional or a beginner who can't wait to start your data science path. This is an important resource for staying current in the data-driven era. It includes the most popular keywords and methods that define the field of data science right now.