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
DATA INTEGRATION Data integration involves combining data residing in different sources and providing users with a unified view of these data. This process becomes significant in a variety of situations‚ which include both commercial (when two similar companies need to merge their databases and scientific (combining research results from different bioinformatics repositories‚ for example) domains. Data integration appears with increasing frequency as the volume and the need to share existing data explodes
Premium Data mining Data analysis
Residuals Date: _____________________ Introduction The fit of a linear function to a set of data can be assessed by analyzing__________________. A residual is the vertical distance between an observed data value and an estimated data value on a line of best fit. Representing residuals on a___________________________ provides a visual representation of the residuals for a set of data. A residual plot contains the points: (x‚ residual for x). A random residual plot‚ with both
Premium Statistics Regression analysis Mathematics
Tatiana Safonova-Lynn. TASK 1 – FINANCIAL STATEMENT ANALYSIS AND CONTROLS Requirements for Task 1: A. Prepare a summary report in which you do the following: 1. Evaluate the company’s operational strengths and weaknesses based on the following: In order to evaluate company’s operational strength and weaknesses accurately it is important to have access to more than one year worth of data. The company‚ of course‚ will not be evaluated on the basis of couple of ratios‚ it is very important to analyze
Premium
1 Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data
Premium Data analysis Business intelligence Data
Lab – Data Analysis and Data Modeling in Visio Overview In this lab‚ we will learn to draw with Microsoft Visio the ERD’s we created in class. Learning Objectives Upon completion of this learning unit you should be able to: ▪ Understand the concept of data modeling ▪ Develop business rules ▪ Develop and apply good data naming conventions ▪ Construct simple data models using Entity Relationship Diagrams (ERDs) ▪ Develop entity relationships and define
Premium Entity-relationship model
1. There are 2 different types of switching‚ circuit switching and packet switching. a. Circuit Switching – One wire connects multiple destinations through communication nodes which creates a dedicated channel with full bandwidth available for communication. b. Packet Switching – Groupings of transmitted data are converted into smaller packets that are sent over a network. The transmission resources are allocated as needed and a connection exists only as long as the transmission is sent. 2.
Premium Investment Risk aversion Risk
IT208 – Systems Analysis and Design 1 IT208 – Case Study Document Outline Title Page Abstract Table of Contents List of Figures List of Tables 1.0 Research Description (January 22‚ 2013) 1.1 Overview of the Current State of Technology 1.2 Problem Analysis of the Existing System 2.0 Research Objectives (January 29‚ 2013) 2.1 General Objective 2.2 Specific Objectives 3.0 Scope and Limitation of the Research (February 4‚ 2013) 4.0 Research Methodology (February 4‚ 2013) 5.0 The System (included
Premium 1980 1969 1967
Data Acquisition and Interfacing Lecture 09 Introduction A data acquisition system consists of many components that are integrated to: • Sense physical variables (use of transducers) • Condition the electrical signal to make it readable by an A/D board • Convert the signal into a digital format acceptable by a computer • Process‚ analyze‚ store‚ and display the acquired data with the help of software Data Acquisition System Block Diagram Flow of information in DAQ 1. 2.
Premium Digital Digital signal processing Data acquisition
Dynamic Dependency Analysis of Ordinary Programs 1 Todd M. Austin and Gurindar S. Sohi Computer Sciences Department University of Wisconsin-Madison 1210 W. Dayton Street Madison‚ WI 53706 faustin sohig@cs.wisc.edu A quantitative analysis of program execution is essential to the computer architecture design process. With the current trend in architecture of enhancing the performance of uniprocessors by exploiting ne-grain parallelism‚ rst-order metrics of program execution‚ such as operation frequencies
Premium Central processing unit Computer program