An Executive Guide to Data Management

While you work hard building your startup, one of the biggest challenges you’ll face will be around your product’s ability to solve a big enough problem and its success in the market. Agile Analytics for Startups will help you navigate the complexity of early-stage business analytics, performance measurement, and the metrics that matter to your company. You can use the proven frameworks in this book to validate your product idea and the product/market fit, and understand your customers more granularly while you scale your business for automation. You can test and use many tools and solutions provided in the book and interact with different features of those solutions as you engage with other users of those products. This book will provide you with a step-by-step framework, examples and powerful solutions, from ideation to growth and all the way to scaling your business as you build your company with the power of analytics. - Agility is your advantage over large companies - Understand business analytics essentials and define how you will measure the success of your business early - Once you define your solution for “the problem” you tackle, validate your customer - Keep a short list of KPIs for the success of your product - Engage your customers throughout the development cycle - Product/market fit should happen before you go to market big - Keep testing your product, reiterate continuously - Know when to pivot as you modify and optimize your roadmap - Be ready to speed up and maximize your output before the significant funding milestone(s)

This new Edition of Electronic Commerce is a complete update of the leading graduate level/advanced undergraduate level textbook on the subject. Electronic commerce (EC) describes the manner in which transactions take place over electronic networks, mostly the Internet. It is the process of electronically buying and selling goods, services, and information. Certain EC applications, such as buying and selling stocks and airline tickets online, are reaching maturity, some even exceeding non-Internet trades. However, EC is not just about buying and selling; it also is about electronically communicating, collaborating, and discovering information. It is about e-learning, e-government, social networks, and much more. EC is having an impact on a significant portion of the world, affecting businesses, professions, trade, and of course, people. The most important developments in EC since 2014 are the continuous phenomenal growth of social networks, especially Facebook , LinkedIn and Instagram, and the trend toward conducting EC with mobile devices. Other major developments are the expansion of EC globally, especially in China where you can find the world's largest EC company. Much attention is lately being given to smart commerce and the use of AI-based analytics and big data to enhance the field. Finally, some emerging EC business models are changing industries (e.g., the shared economy models of Uber and Airbnb). The 2018 (9th) edition, brings forth the latest trends in e-commerce, including smart commerce, social commerce, social collaboration, shared economy, innovations, and mobility.

Data Science is one of the "sexiest jobs of the 21st Century", but few resources are geared towards learners with no prior experience. Getting Started in Data Science simplifies the core of the concepts of Data Science and Machine Learning. This book includes perspectives of a Data Science from someone with a non-traditional route to a Data Science career. Getting Started in Data Science creatively weaves in ethical questions and asks readers to question the harm models can cause as they learn new concepts. Unlike many other books for beginners, this book covers bias and accountability in detail as well as career insight that informs readers of what expectations are in industry Data Science.

Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following: • Data governance perceptions and challenges • Key considerations when implementing data governance to achieve and sustain success• Strategy and data governance• Different data governance maturity frameworks• Data governance – people and process elements• Data governance metrics This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects.

The ChatGPT Money Guide offers valuable insights and strategies for quickly and easily making money using ChatGPT, an advanced chatbot technology. The book guides readers through various aspects of building an online presence, identifying their skills, and creating a game plan for success. It explores different ways to utilize ChatGPT for passive income, including monetizing conversations, building ChatGPT-powered products, and offering freelancing and consulting services. The guide also delves into e-commerce and affiliate marketing strategies, content creation and monetization, maximizing productivity with ChatGPT, scaling an online business, diversifying income streams, and monetizing ChatGPT skills. Additionally, it addresses ethical and legal considerations and provides solutions to common challenges in making money with ChatGPT. The book concludes by encouraging readers to reflect on their money-making journey, map out future opportunities, and take action to achieve financial success.