t e r 7 MANAGING DATA RESOURCES 7.1 © 2002 by Prentice Hall LEARNING OBJECTIVES • COMPARE TRADITIONAL FILE ORGANIZATION & MANAGEMENT TECHNIQUES • DESCRIBE HOW DATABASE MANAGEMENT SYSTEM ORGANIZES INFORMATION * 7.2 © 2002 by Prentice Hall LEARNING OBJECTIVES • IDENTIFY TYPES OF DATABASE‚ PRINCIPLES OF DATABASE DESIGN • DISCUSS DATABASE TRENDS * 7.3 © 2002 by Prentice Hall MANAGEMENT CHALLENGES • TRADITIONAL DATA FILE ENVIRONMENT • DATABASE APPROACH TO DATA MANAGEMENT • CREATING DATABASE
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Problems: Figure 1 shows the frequency domain function for a single square pulse. The signal pulse could represent a digital 1 in a communications system. Note that an infinite number of higher frequencies of decreasing magnitudes is needed to represent the single pulse. What implication does that have for a real digital transmission system? Suppose that a digitised TV picture is to be transmitted from a source that uses a matrix of 480 x 500 picture elements (pixels)‚ where each pixel can
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BCSCCS 303 R03 DATA STRUCTURES (Common for CSE‚ IT and ICT) L T P CREDITS 3 1 0 4 UNIT - I (15 Periods) Pseudo code & Recursion: Introduction – Pseudo code – ADT – ADT model‚ implementations; Recursion – Designing recursive algorithms – Examples – GCD‚ factorial‚ fibonnaci‚ Prefix to Postfix conversion‚ Tower of Hanoi; General linear lists – operations‚ implementation‚ algorithms UNIT - II (15 Periods)
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difference between Data‚ Information and Knowledge? Data‚ information and knowledge are often referred to and used to represent the same thing. However‚ each term has its own meaning. By defining what data‚ information and knowledge mean individually‚ a greater understanding can be reached. It is also important to look at how they interact with each other. Knowledge‚ by definition‚ is the theoretical or practical understanding of a subject. It is the acquisition of information through education
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5.3.3 Data cleaning Data cleaning helps to remove all unnecessary data. Data cleaning attempts to fill in missing values‚ smooth out noise while identifying outliers and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation. 5.3.4 Data analysis Data analysis is also known as analysis of data or data analytics‚ is a process of inspecting‚ cleansing‚ transforming and modeling data with the goal of discovering
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When Antivirus Software Cripples your Computers What management‚ organization‚ and technology were responsible for the problem? What was the business impact of this software problem‚ both for McAfee and for its customer? If you were a McAfee enterprise customer‚ would you consider McAfee’s response to the problem be acceptable? Why or why not? What should McAfee do in the future to avoid similar problems? How Secure is the Cloud? What security and control problems are described in this
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believes that the maturation of the Internet will allow more and more computing task to be performed via the Web‚ on computers sitting in data center rather than on the desktop. This idea is known as cloud computing‚ and it is central to Google’s business model going forward. Microsoft grew to its giant stature on the strength of its Windows operating system and Office desktop productivity applications‚ which are used by 500 million people worldwide. Sometimes vilified for its anti competitive
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Simply use statistics as a tool. You will be given a data. (Next year you will not be given data‚ you will gather data yoruself). 1. Data: one of the variables is dependent and other dependent. Can be multiple. Then do regression analysis. ANOVA for overall significance and Regression equation. And write based on ANOVA there is a significance or not. 2. Some comments on correlation: volume vs. horse power etc. 3. Hypothesis test of one population. I assume that the mean is etc etc. Small paragraph
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Using the Standard Deviation You made a number of observations about the data sets for the school activities. You used mean and median to measure the center of the data‚ and you used the interquartile range (IQR) to measure the spread. When outliers are present‚ the median and IQR are used to measure center and spread because they are unaffected by extreme values. When the data appears to be symmetric and there are no known outliers‚ the mean and standard deviation (another measure of spread)
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and Kimball’s definition of Data Warehousing. Bill Inmon advocates a top-down development approach that adapts traditional relational database tools to the development needs of an enterprise wide data warehouse. From this enterprise wide data store‚ individual departmental databases are developed to serve most decision support needs. Ralph Kimball‚ on the other hand‚ suggests a bottom-up approach that uses dimensional modeling‚ a data modeling approach unique to data warehousing. Rather than building
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