Download or read book Data Science and Analytics Strategy written by Kailash Awati and published by CRC Press. This book was released on 2023-04-05 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes how to establish data science and analytics capabilities in organisations using Emergent Design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment. Based on their experiences and those of a number of data leaders, the authors provide actionable advice on data technologies, processes, and governance structures so that readers can make choices that are appropriate to their organisational contexts and requirements. The book blends academic research on organisational change and data science processes with real-world stories from experienced data analytics leaders, focusing on the practical aspects of setting up a data capability. In addition to a detailed coverage of capability, culture, and technology choices, a unique feature of the book is its treatment of emerging issues such as data ethics and algorithmic fairness. Data Science and Analytics Strategy: An Emergent Design Approach has been written for professionals who are looking to build data science and analytics capabilities within their organisations as well as those who wish to expand their knowledge and advance their careers in the data space. Providing deep insights into the intersection between data science and business, this guide will help professionals understand how to help their organisations reap the benefits offered by data. Most importantly, readers will learn how to build a fit-for-purpose data science capability in a manner that avoids the most common pitfalls.

Download or read book Data Science Strategy For Dummies written by Ulrika Jägare and published by John Wiley & Sons. This book was released on 2019-06-12 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.

Download or read book Data Strategy written by Bernard Marr and published by Kogan Page Publishers. This book was released on 2017-04-03 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category Less than 0.5 per cent of all data is currently analyzed and used. However, business leaders and managers cannot afford to be unconcerned or sceptical about data. Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Data Strategy is a must-have guide to creating a robust data strategy. Explaining how to identify your strategic data needs, what methods to use to collect the data and, most importantly, how to translate your data into organizational insights for improved business decision-making and performance, this is essential reading for anyone aiming to leverage the value of their business data and gain competitive advantage. Packed with case studies and real-world examples, advice on how to build data competencies in an organization and crucial coverage of how to ensure your data doesn't become a liability, Data Strategy will equip any organization with the tools and strategies it needs to profit from Big Data, analytics and the Internet of Things (IoT).

Download or read book Business Intelligence Strategy and Big Data Analytics written by Steve Williams and published by Morgan Kaufmann. This book was released on 2016-04-08 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like “big data and “big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. Provides ideas for improving the business performance of one’s company or business functions Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans

Download or read book Data Science for Marketing Analytics written by Mirza Rahim Baig and published by Packt Publishing Ltd. This book was released on 2021-09-07 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Minding the Machines written by Jeremy Adamson and published by John Wiley & Sons. This book was released on 2021-06-25 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success. In this book, you’ll discover: A focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics team Repeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commit The importance of creating clear goals and objectives when creating a new analytics unit in an organization Perfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, Minding the Machines is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team’s overall results.

Download or read book Data Strategy written by Sid Adelman and published by Addison-Wesley Professional. This book was released on 2005 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Without a data strategy, the people within an organization have no guidelines for making decisions that are absolutely crucial to the success of the IT organization and to the entire organization. The absence of a strategy gives a blank check to those who want to pursue their own agendas, including those who want to try new database management systems, new technologies (often unproven), and new tools. This type of environment provides no hope for success. Data Strategy should result in the development of systems with less risk, higher quality systems, and reusability of assets. This is key to keeping cost and maintenance down, thus running lean and mean. Data Strategy provides a CIO with a rationale to counter arguments for immature technology and data strategies that are inconsistent with existing strategies. This book uses case studies and best practices to give the reader the tools they need to create the best strategy for the organization.

Download or read book Big Data Science Analytics written by Arshdeep Bahga and published by Vpt. This book was released on 2016-04-15 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. We have written this textbook to meet this need at colleges and universities, and also for big data service providers.

Download or read book Data Science for Business written by Foster Provost and published by "O'Reilly Media, Inc.". This book was released on 2013-07-27 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Download or read book Using Strategy Analytics to Measure Corporate Performance and Business Value Creation written by Kautish, Sandeep and published by IGI Global. This book was released on 2021-06-25 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Strategic analytics is a relatively new field in conjunction with strategic management and business intelligence. Generally, the strategic management field deals with the enhancement of the decision-making capabilities of managers. Typically, such decision-making processes are heavily dependent upon various internal and external reports. Managers need to develop their strategies using clear strategy processes supported by the increasing availability of data. This situation calls for a different approach to strategy, including integration with analytics, as the science of extracting value from data and structuring complex problems. Using Strategy Analytics to Measure Corporate Performance and Business Value Creation discusses how to tackle complex business dynamics using optimization techniques and modern business analytics tools. It covers not only introductory concepts of strategic analytics but also provides strategic analytics applications in each area of management such as market dynamics, customer analysis, operations, and people management. It unveils the best industry practices and how managers can become expert strategists and analysts to better measure and enhance corporate performance and their businesses. This book is ideal for analysts, executives, managers, entrepreneurs, researchers, students, industry professionals, stakeholders, practitioners, academicians, and others interested in the strategic analytics domain and how it can be applied to complex business dynamics.

Download or read book Strategic Analytics written by Martin Kunc and published by John Wiley & Sons. This book was released on 2018-11-13 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defines common ground at the interface of strategy and management science and unites the topics with an original approach vital for strategy students, researchers and managers Strategic Analytics: Integrating Management Science and Strategy combines strategy content with strategy process through the lenses of management science, masterfully defining the common ground that unites both fields. Each chapter starts with the perspective of a certain strategy problem, such as competition, but continues with an explanation of the strategy process using management science tools such as simulation. Facilitating the process of strategic decision making through the lens of management science, the author integrates topics that are usually in conflict for MBAs: strategy and quantitative methods. Strategic Analytics features multiple international real-life case studies and examples, business issues for further research and theory review questions and exercises at the end of each chapter. Strategic Analytics starts by introducing readers to strategic management. It then goes on to cover: managerial capabilities for a complex world; politics, economy, society, technology, and environment; external environments known as exogenous factors (PESTE) and endogenous factors (industry); industry dynamics; industry evolution; competitive advantage; dynamic resource management; organisational design; performance measurement system; the life cycle of organisations from start-ups; maturity for maintaining profitability and growth; and finally, regeneration. Developed from the author's own Strategy Analytics course at Warwick Business School, personal experience as consultant, and in consultation with other leading scholars Uses management science to facilitate the process of strategic decision making Chapters structured with chapter objectives, summaries, short case studies, tables, student exercises, references and management science models Accompanied by a supporting website Aimed at both academics and practitioners, Strategic Analytics is an ideal text for postgraduates and advanced undergraduate students of business and management.

Download or read book Data and Analytics Strategy for Business written by Simon Asplen-Taylor and published by Kogan Page Publishers. This book was released on 2022-06-03 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business. Most businesses have a wealth of data buried in their systems which, if used effectively, could increase revenue, reduce costs and risk and improve customer satisfaction and employee experience. Beginning with how to choose projects which reflect your organization's goals and how to make the business case for investing in data, this book then takes the reader through the five 'waves' of organizational data maturity. It takes the reader from getting started on the data journey with some quick wins, to how data can help your business become a leading innovator which systematically outperforms competitors. Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making. Filled with real-world examples and case studies, this book is a stage-by-stage guide to designing and implementing a results-driven data strategy.

Download or read book Big Data MBA written by Bill Schmarzo and published by John Wiley & Sons. This book was released on 2015-12-11 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

Download or read book Data Science For Dummies written by Lillian Pierson and published by John Wiley & Sons. This book was released on 2021-08-20 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Science for Marketing Analytics written by Tommy Blanchard and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.

Download or read book Citizen Gain written by Heather Harris and published by . This book was released on 2018-05-29 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the playbook you've been waiting for. Ms. Harris reaches beyond the hype to give you practical, actionable insights that you can use today to equip your analysts to become Citizen Data Scientists -- powerful, front-line players who are powerful catalysts for your overall data science strategy. Learn how to bring your data scientists and analysts together to practice data science as a team sport.CATALYZING THE MODERN ANALYTICS REVOLUTIONThe analytics hype is officially at fever pitch, but today's organizations still struggle to harness modern analytics tools in a way that actually makes a difference for the business. If you're skeptical that doing another deployment and hiring more data scientists is going to move the needle, what's the answer instead?Step forward into a modern analytics capability by developing and unleashing the power of Citizen Data Scientists across your enterprise. Your Center of Excellence may be world class, but it can't scale fast enough to meet demand from the business. Empower both your analysts and data scientists in a way that allows Data Science to yield its greatest gains when practiced as a team sport.

Download or read book Big Data and Analytics written by Vincenzo Morabito and published by Springer. This book was released on 2015-01-31 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.