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Alan R. Simon

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Data Analytics & Visualization All-in-One For Dummies

Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.

Data Lakes For Dummies

Take a dive into data lakes “Data lakes” is the latest buzz word in the world of data storage, management, and analysis. Data Lakes For Dummies decodes and demystifies the concept and helps you get a straightforward answer the question: “What exactly is a data lake and do I need one for my business?” Written for an audience of technology decision makers tasked with keeping up with the latest and greatest data options, this book provides the perfect introductory survey of these novel and growing features of the information landscape. It explains how they can help your business, what they can (and can’t) achieve, and what you need to do to create the lake that best suits your particular needs. With a minimum of jargon, prolific tech author and business intelligence consultant Alan Simon explains how data lakes differ from other data storage paradigms. Once you’ve got the background picture, he maps out ways you can add a data lake to your business systems; migrate existing information and switch on the fresh data supply; clean up the product; and open channels to the best intelligence software for to interpreting what you’ve stored. Understand and build data lake architecture Store, clean, and synchronize new and existing data Compare the best data lake vendors Structure raw data and produce usable analytics Whatever your business, data lakes are going to form ever more prominent parts of the information universe every business should have access to. Dive into this book to start exploring the deep competitive advantage they make possible—and make sure your business isn’t left standing on the shore.

SQL: 1999

SQL: 1999 is the best way to make the leap from SQL-92 to SQL:1999, but it is much more than just a simple bridge between the two. The latest from celebrated SQL experts Jim Melton and Alan Simon, SQL:1999 is a comprehensive, eminently practical account of SQL's latest incarnation and a potent distillation of the details required to put it to work. Written to accommodate both novice and experienced SQL users, SQL:1999 focuses on the language's capabilities, from the basic to the advanced, and the ways that real applications take advantage of them. Throughout, the authors illustrate features and techniques with clear and often entertaining references to their own custom database. Gives authoritative coverage from an expert team that includes the editor of the SQL-92 and SQL:1999 standards. Provides a general introduction to SQL that helps you understand its constituent parts, history, and place in the realm of computer languages. Explains SQL:1999's more sophisticated features, including advanced value expressions, predicates, advanced SQL query expressions, and support for active databases. Explores key issues for programmers linking applications to SQL databases. Provides guidance on troubleshooting, internationalization, and changes anticipated in the next version of SQL. Contains appendices devoted to database design, a complete SQL:1999 example, the standardization process, and more.

Data Warehousing And Business Intelligence For e-Commerce

You go online to buy a digital camera. Soon, you realize you've bought a more expensive camera than intended, along with extra batteries, charger, and graphics software-all at the prompting of the retailer. Happy with your purchases? The retailer certainly is, and if you are too, you both can be said to be the beneficiaries of "customer intimacy" achieved through the transformation of data collected during this visit or stored from previous visits into real business intelligence that can be exercised in real time. Data Warehousing and Business Intelligence for e-Commerce is a practical exploration of the technological innovations through which traditional data warehousing is brought to bear on this and other less modest e-commerce applications, such as those at work in B2B, G2C, B2G, and B2E models. The authors examine the core technologies and commercial products in use today, providing a nuts-and-bolts understanding of how you can deploy customer and product data in ways that meet the unique requirements of the online marketplace-particularly if you are part of a brick-and-mortar company with specific online aspirations. In so doing, they build a powerful case for investment in and aggressive development of these approaches, which are likely to separate winners from losers as e-commerce grows and matures. * Includes the latest from successful data warehousing consultants whose work has encouraged the field's new focus on e-commerce. * Presents information that is written for both consultants and practitioners in companies of all sizes. * Emphasizes the special needs and opportunities of traditional brick-and-mortar businesses that are going online or participating in B2B supply chains or e-marketplaces. * Explains how long-standing assumptions about data warehousing have to be rethought in light of emerging business models that depend on customer intimacy. * Provides advice on maintaining data quality and integrity in environments marked by extensive customer self-input. * Advocates careful planning that will help both old economy and new economy companies develop long-lived and successful e-commerce strategies. * Focuses on data warehousing for emerging e-commerce areas such as e-government and B2E environments.