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38536 results in Cambridge Textbooks

Page 1176 of 1927

  • 16 - Data Distribution and Distributed Transaction Management

  • 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 516-548

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • grasp the basics of distributed systems and distributed databases;

  • • discern key architectural implications of distributed databases;

  • • understand the impact of fragmentation, allocation, and replication;

  • • identify different types of transparency;

  • • understand the steps in distributed query processing;

  • • understand distributed transaction management and concurrency control;

  • • grasp the impact of eventual consistency and BASE transactions.

    • Opening Scenario

    As Sober envisions growing as part of its long-term strategy, it wants to have a careful understanding of the data implications involved. More specifically, the company wants to know if it would make sense to distribute its data across a network of offices and work with a distributed database. Sober wants to know the impact of data distribution on query processing and optimization, transaction management, and concurrency control.

    In this chapter, we focus on the specifics of distributed databases (i.e., systems in which the data and DBMS functionality are distributed over different nodes or locations on a network). First, we discuss the general properties of distributed systems and offer an overview of some architectural variants of distributed database systems. Then, we tackle the different ways of distributing data over nodes in a network, including the possibility of data replication. We also focus on the degree to which the data distribution can be made transparent to applications and users. Then, we discuss the complexity of query processing and query optimization in a distributed setting. A next section is dedicated to distributed transaction management and concurrency control, focusing on both tightly coupled and loosely coupled settings. The last section overviews the particularities of transaction management in Big Data and NoSQL databases, which are often distributed in a cluster set-up, presenting BASE transactions as an alternative to the traditional ACID transaction paradigms.

    Distributed Systems and Distributed Databases

    Ever since the early days of computing, which were dominated by monolithic mainframes, distributed systems have had their place in the ICT landscape. A distributed computing system consists of several processing units or nodes with a certain level of autonomy, which are interconnected by a network and which cooperatively perform complex tasks. These complex tasks can be divided into subtasks as performed by the individual nodes.

  • 1 - Basic Concepts

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 4-19

  • Summary

    This chapter introduces basic concepts needed for the study and description of morphologically complex words. Since this is a book about the particular branch of morphology called word-formation, we first take a look at the notion of ‘word.’ We then turn to a first analysis of the kinds of phenomena that fall into the domain of word-formation, before we finally discuss how word-formation can be distinguished from the other sub-branch of morphology, inflection.

  • 1 - About Innovation and Entrepreneurship

  • Dick Whittington, University of York
  • Book:
    Digital Innovation and Entrepreneurship
    Published online:
    06 December 2018
    Print publication:
    12 July 2018, pp 1-51

  • Summary

    Innovation is about ideas and their exploitation through product and service offerings: creativity and imagination are crucial to success, as are questioning, testing and incisiveness. An entrepreneur has talent and determination to turn an innovation into a sustainable business: they work with a risk profile ranging across people, technology, systems, the marketplace and the economic landscape. Knowledge, skills and connections with these domains must be built, hired and purchased for successful delivery of innovation. Succeeding in the design, operation and growth of a business needs a blend of innovation and entrepreneurship, and the balance needed changes over time. This chapter first addresses aspects of innovation: • Innovation process – how ideas become successful business offerings • Ecosystem – the importance of locating innovation in a market context • Types of innovation – and the market impact of each type • Historical context – longer-term models of development • Innovators – parties involved and their motivations It concludes by addressing the principal ingredients for success, and the most common reasons for failure in innovation and entrepreneurship.

  • 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.

  • 1 - Basic Concepts

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 4-19

  • Summary

    This chapter introduces basic concepts needed for the study and description of morphologically complex words. Since this is a book about the particular branch of morphology called word-formation, we first take a look at the notion of ‘word.’ We then turn to a first analysis of the kinds of phenomena that fall into the domain of word-formation, before we finally discuss how word-formation can be distinguished from the other sub-branch of morphology, inflection.

  • 20 - Analytics

  • 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 664-730

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • understand the key steps of the analytics process model;

  • • identify the skill set of a data scientist;

  • • preprocess data for analytics using denormalization, sampling, exploratory data analysis, and dealing with missing values and outliers;

  • • build predictive analytical models using linear regression, logistic regression, and decision trees;

  • • evaluate predictive analytical models by splitting up the dataset and using various performance metrics;

  • • build descriptive analytical models using association rules, sequence rules, and clustering;

  • • understand the basic concepts of social network analytics;

  • • discern the key activities during post-processing of analytical models;

  • • identify the critical success factors of analytical models;

  • • understand the economic perspective on analytics by considering the total cost of ownership (TCO) and return on investment (ROI) and how they are affected by in- versus outsourcing, on-premise versus cloud solutions, and open versus commercial software;

  • • improve the ROI of analytics by exploring new sources of data, increasing data quality, securing management support, optimizing organizational aspects, and fostering cross-fertilization;

  • • understand the impact of privacy and security in a data storage, processing, and analytics context.

    • Opening Scenario

    Now that Sober has made its first steps in business intelligence, it is eager to take this to the next level and explore what it could do with analytics. The company has witnessed extensive press and media coverage on predictive and descriptive analytics and wonders what these technologies entail and how they could be used to its advantage. It is actually thinking about analyzing its booking behavior, but is unsure how to tackle this. Given that Sober is a startup, it also wants to know the economic and privacy implications of leveraging these technologies.

    In this chapter, we extensively zoom into analytics. We kick-off by providing a bird's eye overview of the analytics process model. We then give examples of analytics applications and discuss the data scientist job profile. We briefly zoom into data pre-processing. The next section elaborates on different types of analytics: predictive analytics, descriptive analytics, and social network analytics. We also discuss the post-processing of analytical models. Various critical success factors for analytical models are clarified in the following section. This is followed by a discussion on the economic perspective of analytics.

Page 1176 of 1927