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Contents Should we tell you the whole story? Of course, there is an inevitable tension in trying to work like this. For example, in Chapter 16 we talk about referential integrity. There are - sentially six different flavors of referential integrity but Access only s- ports four of them (they are the most important ones however, so you aren’t missing out on too much). The problem is this. Should we tell you about the other two? If we do, as an Access user you have every right to be annoyed that we are telling you about a feature you can’t use. On the other hand, the six different types that we describe are part of the re- tional world and this book is about that world – we are not tryin...
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You'll Learn Become fluent in the essential concepts and terminology of data science and data engineering Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers
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This module of the handbook concentrates on the integration and migration strategies and technologies. Topics include strategic issues in integration versus migration, Enterprise Application Integration (EAI), B2B integration, EAI/eAI platforms, data warehousing for integration, migration strategies and replacements with ERPs.