Outline Introduction Distributed DBMS Architecture Distributed Database Design Distributed Query Processing Distributed Transaction Management Data Replication Consistency criteria Update propagation protocols Parallel Database Systems Data Integration Systems Web Search/Querying Peer-to-Peer Data Management Data Stream Management Distributed & Parallel DBMS M. Tamer Özsu Page 6.1 Acknowledgements Many of these slides are from notes prepared by Prof. Gustavo
Premium ACID Data management Transaction processing
CHAPTER 12 ROUTING IN SWITCHED NETWORKS A NSWERS TO Q UESTIONS 12.1 The average load expected over the course of the busiest hour of use during the course of a day. 12.2 The tradeoff is between efficiency and resilience. 12.3 A static routing strategy does not adapt to changing conditions on the network but uses a fixed strategy developed ahead of time. With alternate routing‚ there are a number of alternate routes between source and destination and a dynamic choice of routes is
Premium Ethernet Computer networking Computer network
it for any other purpose. DATE: 06/10/2013 Introduction: In data mining it is said that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson‚ 2001‚ p. 26).” Tourism and hospitality industry generates massive amount of data. In each and every transaction there is set of data generated. In tourism and hospitality‚ knowing your customer is very
Premium Data mining
Activity 1 Reasons why organisations need to collect HR Data. It is important for organisations to collect and retain HR data as this will be key for strategic and HR planning. It will also help to have all the information necessary to make informed decisions‚ for the formulation and implementation of employment policies and procedures‚ to monitor fair and consistent treatment of staff‚ to contribute to National Statistics and to comply with statutory requirements. The key organisational
Premium Data Protection Act 1998 Employment Organization
1. Data mart definition A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. Data marts are small slices of the data warehouse. Whereas data warehouses have an enterprise-wide depth‚ the information in data marts pertains to a single department. In some deployments‚ each department or business unit is considered the owner of its data
Premium Data warehouse Data management
IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
Premium Data analysis Data management Data mining
an era of big data‚ this data-driven world has the potential to improve the efficiencies of enterprises and improve the quality of our lives; however‚ there are a number of challenges that must be addressed to allow us to exploit the full potential of big data. This paper focuses on challenges faced by online retailers when making use of big data. With the provided examples of online retailers Amazon and eBay‚ this paper addressed the key challenges of big data analytics including data capture and
Premium Electronic commerce Online shopping Retailing
Data Models Consider a simple student registration. Specifically we want to support the tasks of students registering for or withdrawing from a class. To do this‚ the system will need to record data about what entities? What specific data about the entities will need to be stored? What is the cardinality between students and courses? Diagram the data model. While‚ considering a student class registration system for registering or withdrawing a system must have the capability to record data in
Premium Java Subroutine Class
LECTURE 1 DATA TYPES Our interactions (inputs and outputs) of a program are treated in many languages as a stream of bytes. These bytes represent data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data in various way such as adding them up or sorting them. This data comes in different forms. Examples include: your
Premium Data type
Data collection is any process of preparing and collecting data‚ for example‚ as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record‚ to make decisions about important issues‚ or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project‚ and is often formalized through a data collection plan which often
Premium Scientific method Qualitative research Sampling