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38536 results in Cambridge Textbooks

Page 1179 of 1927

  • Answer Key to Exercises

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 198-229

  • Summary

    This chapter provides answers to the exercises found at the end of each chapter. Where appropriate, the answers include critical discussions of the data, concepts and analyses employed.

  • 9 - Extended Relational Databases

  • from Part II - Types of Database Systems
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 231-254

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • identify the shortcomings of the relational model;

  • • define and use triggers and stored procedures;

  • • understand how RDBMSs can be extended with OO concepts such as user-defined types, user-defined functions, inheritance, behavior, polymorphism, collection types, and large objects;

  • • define and use recursive SQL queries.

    • Opening Scenario

    Now that Sober has decided to continue with its relational model, the company was wondering whether it could enrich it with some smart extensions. It wondered whether it would be possible to make the RDBMS more active so it can autonomously take initiative for action when casespecific situations occur. Although Sober was not entirely convinced about OODBMSs and decided not to continue with them, they appreciate some of the OO concepts introduced. They are wondering whether it would be possible to have a best-of-both-worlds approach, whereby they could enrich their relational model with some of the OO concepts they learned about.

    In this chapter, we revisit RDBMSs, which are very popular in industry. We start by refreshing the key building blocks of the relational model and discuss its limitations. We then look at the ways of extending relational databases, starting with reviewing triggers and stored procedures as two key mechanisms to make RDBMSs more active. Next, we introduce object-relational DBMSs (ORDBMSs). In contrast to the OODBMSs in Chapter 8, ORDBMSs build on a relational engine, but they extend RDBMSs with object-oriented (OO) characteristics. We conclude with recursive queries, which are a powerful extension to the SQL language.

    Limitations of the Relational Model

    The relational data model, and the RDBMS implementations thereof, have been very successful for managing well-structured numerical and alphanumerical data. One of the major reasons for this is the mathematical simplicity and soundness of the relational model. As discussed in Chapter 6, its two key building blocks are tuples and relations. A tuple is a composition of values of attribute types that describe an entity. It can be created by using a tuple constructor. A relation is a mathematical set of tuples describing similar entities. It can be created by using a set constructor. As also mentioned in Chapter 6, the relational model requires all relations to be normalized. Data about entities can be fragmented across multiple relations, which are connected using primary–foreign key relationships.

  • 15 - Accessing Databases and Database APIs

  • from Part III - Physical Data Storage, Transaction Management, and Database Access
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 458-515

  • Summary

    Chapter Objectives

    In this chapter, you will learn:

  • • how database systems can be accessed from the outside world;

  • • what is meant by a database application programming interface (API);

  • • to understand the differences between proprietary versus universal APIs, between embedded versus call-level APIs, and early binding versus late binding;

  • • which universal database application programming interfaces are available to interact with database systems;

  • • how DBMSs play their role within the World Wide Web and the internet.

    • Opening Scenario

    Sober has decided on a relational DBMS vendor, has drawn up the relational schema to implement, and has verified that the database is working as planned by importing sample data and testing some SQL queries. However, a DBMS system does not live in isolation. Sober is planning to develop several applications that will have to connect to its DBMS. For instance, Sober is thinking about a website where customers can book cabs and retrieve their order history, and a mobile app that will have to fetch information from the DBMS. Finally, Sober is also planning to develop a desktop application for the customer support team that will be used internally, but also has to be able to access the same DBMS. Sober is still thinking about different options in terms of programming languages to develop these applications, but wonders how easy it will be for these applications to access the database in order to store and retrieve information from it.

    In this chapter, we take a closer look at the forms of accessing database systems. Naturally, the manner of how a DBMS is interfaced with heavily depends on the system architecture it applies. Accessing a DBMS in a legacy mainframe set-up is different than interfacing with a DBMS in a client–server-based architecture, so we open this chapter with an overview of different database system architectures. Next, we turn our attention toward the different database application programming interfaces, or APIs for short. As the name suggests, a database API exposes an interface through which clients, third-party, and end-user applications can access, query, and manage the DBMS. Finally, we look at DBMSs’ role and place within the World Wide Web, and how recent trends in this landscape are influencing and shaping the requirements imposed on DBMSs.

  • 8 - Leadership and Structure

  • Dick Whittington, University of York
  • Book:
    Digital Innovation and Entrepreneurship
    Published online:
    06 December 2018
    Print publication:
    12 July 2018, pp 331-376

  • Summary

    The leadership team works within a legal structure to deliver business objectives. This implies responsibilities to establish and sustain an organization that values, motivates and rewards its people; to plan and control resources; and to ensure compliance with relevant reporting and taxation regimes. It is important that the leadership team remain aware of their legal duties and of the risks that they carry with respect to those who work within the organization or who participate as investors, shareholders or providers of professional services. Without such awareness both the business and its leaders may be exposed to legal or financial redress. The topics covered by this chapter include: • Requirements and responsibilities of leadership, management and governance – directors, employees and contractors • Financial planning and control – cash management and the setting, balancing and monitoring of budgets • Business structural and legal requirements – corporate, contractual and shareholding structures and agreements The coverage equips the entrepreneur with sufficient understanding of the necessary requirements, options, relevant considerations and principal decisions needed.

  • 19 - Big Data

  • from Part IV - Data Warehousing, Data Governance, and (Big) Data Analytics
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 626-663

  • Summary

    Chapter Objectives

    In this chapter, you will learn:

  • • what is meant by “Big Data” and its “5 Vs”;

  • • to understand the differences between traditional database management systems and Big Data technologies such as Hadoop;

  • • to understand the differences between traditional data warehousing approaches and Big Data technologies;

  • • to identify the tradeoffs when opting to adopt a Big Data stack;

  • • what the links are between Big Data and NoSQL databases.

    • Opening Scenario

    Sober has made its first steps in setting up a data warehouse on top of its existing DBMS stack to kick-start its business intelligence activities, with the main goal of reporting purposes. However, Sober's management is hearing a lot lately about “Big Data” and “Hadoop” with regards to storing and analyzing huge amounts of data. Sober is wondering whether these technologies would offer an added benefit. So far, Sober is happy with its relational DBMS, which integrates nicely with its business intelligence tooling. The mobile development team, meanwhile, has been happy to work with MongoDB, a NoSQL database, to handle the increased workload from mobile users. Hence, the question for Sober is: what would a Big Data stack offer on top of this?

    Data are everywhere. To give some staggering examples, IBM projects that every day we generate 2.5 quintillion bytes of data. Every minute, more than 300,000 tweets are created, Netflix subscribers are streaming more than 70,000 hours of video, Apple users download 30,000 apps, and Instagram users like almost two million photos. In relative terms, 90% of the data in the world have been created in the last two years. These massive amounts of data yield an unprecedented treasure of internal customer knowledge, ready to be analyzed using state-of-the-art analytical techniques to better understand and exploit customer behavior by identifying new business opportunities together with new strategies. In this chapter, we zoom into this concept of “Big Data” and explain how these huge data troves are changing the world of DBMSs. We kick-off by reviewing the 5 Vs of Big Data. Next, we zoom in on the common Big Data technologies in use today. We discuss Hadoop, SQL on Hadoop, and Apache Spark.

  • 4 - Affixation

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 71-104

  • Summary

    This chapter provides an overview of the affixational word-formation processes of English. First, it discusses how affixes can be distinguished from other entities. This is followed by an introduction to the methodological problems of data gathering for the study of affixation through dictionaries and electronic corpora. Then some general properties that characterize the system of English affixation are introduced, and a survey of a wide range of suffixes and prefixes is presented. Finally, we investigate cases of infixation.

  • Glossary

  • Dick Whittington, University of York
  • Book:
    Digital Innovation and Entrepreneurship
    Published online:
    06 December 2018
    Print publication:
    12 July 2018, pp 410-433

  • Summary

    The business world and the digital economy each bring a wide range of specialist terms that are used without explanation. It is important therefore for an entrepreneur to be aware of the terminology that is likely to be used, so that they can contribute knowledgably and with confidence. The glossary provides clear descriptions of the meaning of around 300 specialist terms and abbreviations, ranging from Actor, Actual Market Value and Adaptive customization, through Monthly Recurring Revenue (MRR), Multisided platforms and Net Fee Income (NFI), to Vesting, Virtual reality (VR), White labelling and the World Intellectual Property Organization (WIPO). The glossary is included as an integral part of the book for easy reference, and is also available as an ancillary resource on the companion website.

  • 5 - Value Capture

  • Dick Whittington, University of York
  • Book:
    Digital Innovation and Entrepreneurship
    Published online:
    06 December 2018
    Print publication:
    12 July 2018, pp 193-231

  • Summary

    A business meets its objectives by creating value, both for its customers and for itself: this chapter is about the process of capturing value into the business to feed sustainability, development and growth. This chapter addresses the following: • Setting a strategy for value capture – defining objectives, assessing competitive, collaborative and negotiation implications of market forces and creating a return-on-investment (ROI) case • Defining what will be offered to the customer – evaluating licensing and service definition options –assumed purchasing process – capex or opex and payment terms • Creating and calibrating a pricing structure – cost plus pricing, demand or value based pricing, dynamic pricing, competition-based pricing, skimming and penetration pricing, freemium pricing, free and open source pricing – bundling, banding, trial period, discounts, optional features • Drivers of business valuation and principal methods – accounting valuation, asset-based valuation, market valuation, sales and profit multiples, strategic valuation Principles, considerations and techniques are introduced and illustrated using a collection of real-world examples and rolling exemplar.

Page 1179 of 1927