...of result” - Mr. Reyes Example IPT context table Information system title Hungry Jacks information system Environment Hungry Jacks Hinchinbrook Purpose To provide the customer with the ability to efficiently order their food themselves Information Processes -Customer needs to go to plasma screen -Customers selects food -Customers pay -etc Information Technology Data information Participants Touch screen card reader OS Food options Payment options A cruise liner requires a system that tracks passengers who have either embarked or disembarked from the ship Information System Title Cruise Liner information tracking system Environment A cruise liner Purpose To efficiently track passengers who have either embarked or disembarked from the ship Information Processes -Passengers will have a designated member card used to identify them individually -Collects data from user swiping card -Passengers will swipe their cards to sign out of the cruise once their cruise has ended -information will be stored in company servers Information Technology Data Information Participants Card readers Cards Barriers Card reading software Identity Cruise Passengers Location Time scanned Components of an Information System Purpose What it does, how is it used? Information processes Collecting, organising, analysing, storing and retrieving, transmitting and receiving...
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...www.it-ebooks.info MapReduce Design Patterns Donald Miner and Adam Shook www.it-ebooks.info MapReduce Design Patterns by Donald Miner and Adam Shook Copyright © 2013 Donald Miner and Adam Shook. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://my.safaribooksonline.com). For more information, contact our corporate/ institutional sales department: 800-998-9938 or corporate@oreilly.com. Editors: Andy Oram and Mike Hendrickson Production Editor: Christopher Hearse Proofreader: Dawn Carelli Cover Designer: Randy Comer Interior Designer: David Futato Illustrator: Rebecca Demarest December 2012: First Edition Revision History for the First Edition: 2012-11-20 First release See http://oreilly.com/catalog/errata.csp?isbn=9781449327170 for release details. Nutshell Handbook, the Nutshell Handbook logo, and the O’Reilly logo are registered trademarks of O’Reilly Media, Inc. MapReduce Design Patterns, the image of Père David’s deer, and related trade dress are trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O’Reilly Media, Inc., was aware of a trade‐ mark claim, the...
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...governmental sectors is insatiable. The commercial aspect can be anything from security for your home to selling products on the internet. The desire for more information about consumers drives businesses to seek out more direct ways to target their customers and sell more products. This can be something as simple and personal as recommendations from websites such as Amazon, or Netflix (p. 42, Farren &ump; Gibb, 2007). Super markets use club/loyalty cards which provide discounts in exchange for tracking a person's or households purchases. All of these purchases are matched up to someones name and address. This information can than be cross checked with other records that can form an image of a person (p. 41, Farren &ump; Gibb, 2007) . This data can be sold or mined and reconfigured, it has even provided a tool to be used for political purposes. The political side of consumer purchases allow for direct targeting by political parties such as the Bush campaign in 2004 (p. 43, Farren &ump; Gibb, 2007). Membership in political parties has always been an matter of public record but what is not is more personal characteristics and habits. What one party can do to raise funds and turn out the vote another could use to intimidate or suppress by targeting the opposition. What can be seen as the height of this kind of targeting and information is Acxiom with its depth and reach in information...
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...and popular algorithm in clustering and was published in 1955, 50 years ago. The advancement in technology has led to many high-volume, high-dimensional data sets. These huge data sets provide opportunity for automatic data analysis, classification...
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...Social Media Data: Network Analytics meets Text Mining Killian Thiel Tobias Kötter Dr. Michael Berthold Dr. Rosaria Silipo Phil Winters Killian.Thiel@uni-konstanz.de Tobias.koetter@uni-konstanz.de Michael.Berthold@uni-konstanz.de Rosaria.Silipo@KNIME.com Phil.Winters@KNIME.com Copyright © 2012 by KNIME.com AG all rights reserved Revision: 120403F page 1 Table of Contents Creating Usable Customer Intelligence from Social Media Data: Network Analytics meets Text Mining............................................................................................................................................ 1 Summary: “Water water everywhere and not a drop to drink” ............................................................ 3 Social Media Channel-Reporting Tools. .................................................................................................. 3 Social Media Scorecards .......................................................................................................................... 4 Predictive Analytic Techniques ............................................................................................................... 4 The Case Study: A Major European Telco. ............................................................................................. 5 Public Social Media Data: Slashdot ......................................................................................................... 6 Text Mining the Slashdot Data ..........
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...Auditing Standards and Practices Council Philippine Auditing Practice Statement 1009 COMPUTER-ASSISTED AUDIT TECHNIQUES PAPS 1009 PHILIPPINE AUDITING PRACTICE STATEMENT 1009 COMPUTER-ASSISTED AUDIT TECHNIQUES CONTENTS Paragraphs Introduction Description of Computer Assisted Audit Techniques (CAATs) Considerations in the Use of CAATs Using CAATs Using CAATs in Small Entity IT Environments Effective Date Acknowledgment 1-3 4-6 7-16 17-25 26 27 28-29 The Auditing Standards and Practices Council (ASPC) issues Philippine Auditing Practices Statements (PAPS or Statements) to provide practical assistance to auditors in implementing the Philippine Standards on Auditing (PSAs) or to promote good practice. Statements do not have the authority of PSAs. This Statement does not establish any new basic principles or essential procedures; its purpose is to assist auditors, and the development of good practice, by providing guidance on the application of the PSAs regarding the use of Computer Assisted Audit Techniques as an audit tool. This Statement applies to all uses of CAATs involving a computer of any type or size. The auditor exercises professional judgment to determine the extent to which any of the audit procedures described in this Statement may be appropriate in the light of the requirements of the PSAs and the entity’s particular circumstances. PAPS 1009 Introduction 1. The overall objectives and scope of an audit do not change when an audit is conducted in a computer...
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...MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat jeff@google.com, sanjay@google.com Google, Inc. Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Many real world tasks are expressible in this model, as shown in the paper. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of partitioning the input data, scheduling the program’s execution across a set of machines, handling machine failures, and managing the required inter-machine communication. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a large distributed system. Our implementation of MapReduce runs on a large cluster of commodity machines and is highly scalable: a typical MapReduce computation processes many terabytes of data on thousands of machines. Programmers find the system easy to use: hundreds of MapReduce programs have been implemented and upwards of one thousand MapReduce jobs are executed on Google’s clusters every day. 1 Introduction Over the past five years, the authors and many others at...
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...Mgmt 469 Practice Using Stata; Estimating CAPM In this tutorial, you will use monthly returns on several assets to compute stock betas. (The data is from 1978-1987.) Be sure to do steps 1-4. Steps 5-10 require navigating folders. This may prove tricky and can be skipped if you like. 1) You have three options for getting the data. Option (a) is much preferred for now. I will assume that you choose option (a) for this practice project. a) I will send you the data as attachments to an email. You can then save the files to the folder of your choice on the lab computer (or your own computer if you own Stata.) b) You can find the link on the course page. If you choose this option, please save the data to another folder. Do not work with the original data set. cd path:\folder save mycapmfile I will assume you have selected option (a). You should now open Stata (as you would any other program) and then open the capm.dta Stata file (again, as you would with any other file.) 2) Create new variables representing the risk premia for the market and for General Foods ge rpmarket=market-riskfree ge rpgenmills=genmills-riskfree 3) Obtain some summary statistics su riskfree market genmills or, better yet, su riskfree, de (this provides detailed statistics) Which has the highest return? Which has the lowest variance? Are you surprised? 4) Compute beta. Regress rpgmills on rpmarket: regress rpgenmills rpmarket At this point, your Stata screen should look something like the next page (the location...
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...Data Preparation in SPSS Jamie DeCoster Center for Advanced Study of Teaching and Learning University of Virginia 350 Old Ivy Way Charlottesville, VA 22903 August 15, 2012 If you wish to cite the contents of this document, the APA reference for them would be DeCoster, J. (2012). Data Preparation in SPSS. Retrieved from http://www.stat-help.com/notes.html All rights to this document are reserved Table of Contents Version History ............................................................................................................................... 4 Interactive Mode versus Syntax Mode ........................................................................................... 5 Why syntax is typically better..................................................................................................... 5 Getting syntax out of interactive mode commands..................................................................... 5 Best Practices for Data Preparation in SPSS .................................................................................. 7 Use syntax from start to finish .................................................................................................... 7 Maintain accurate codebooks for raw data sets .......................................................................... 7 Use summary data sets for analysis ............................................................................................ 7 Preserve the original...
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...front tire is quickly going flat, and without a spare tube on me, it’s going to be at least an hour walk back to the car. So, what’s the first thing I do? Do I assess my injuries? Get off the trail so the next rider doesn’t run me over? Nope. I pull out my smashed iPhone, cutting my finger on the broken screen to hit “pause” on Strava. No way will I have my time bloated by this idleness. How can I possibly break into the top 10 on the leader board for this segment that way? And once I make top 10—well, King of the Mountain (KoM) is just around the corner… My poor Moots Strava—for those of you who don’t know—is a social fitness application that allows bikers and runners to share, compare, and compete with each other’s personal fitness data. The application lets you track your rides and runs via your iPhone, Android, or GPS device to analyze and quantify your performance and match it against people inside and outside your social circle. I got hooked because Bruce (our director of PM) is hooked. And he’s hooked because Ryan, Tim, and Chris (our developer, QA manager, and lead engineer respectively) are hooked. My Strava Dashboard I’ve been riding the trails at Valley Green for years. Previously, I’ve always seen it as a 17-mile loop with a that you can ride clockwise or counterclockwise. I kept track of my time, focusing on how quickly I could complete the entire loop and how well I was handling the technical challenges. But with Strava, I now see the trails as a series...
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...Follow-on Activity Qualitative Risk Analysis Purpose: Use this follow-on activity to perform a data quality assessment with data of previous projects. Instructions for use: To use this tool, gather historical and lessons-learned risk data from past projects. Then review its accuracy and relevance by evaluating it against a set of listed criteria. Does the data fulfill the criteria or not? Provide a reason. Finally, conclude whether your findings give you confidence in the data. Document your answers in the tables provided. Evaluate how complete the data is |Completeness | |Question |Yes/No |Reasons |Conclusions | |Is the data complete? |Row 2 Column 2 [pic] |Row 2 Column 3 [pic] |Row 2 Column 4 [pic] | |Are charts graphics, and tables completely |Row 3 Column 2 [pic] |Row 3 Column 3 [pic] |Row 3 Column 4 [pic] | |filled in? | | | | For online use, complete each row as described in the instructions. If you would like to work with the page as hard copy, simply print it out using the Print link at the top of this page. Evaluate the data's clarity |Clarity...
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...Derrick Chapman Jr. ITM501- Module I Case November 11, 2013 In review of my position on information overload, there would be no such overload if avenues such as the various social media outlets, informative readings with little or no credibility, and networking forums with no proven success records were not so heavily relied upon within organizations. The course background readings shed light on how social media is hindering the notions of the Data, Information, Knowledge, and Wisdom. Data is defined as unprocessed information, while information is data that has had a chance to be processed, and finally knowledge and wisdom is something that can be reflected upon (Green, P. 2010). If you are constructively processing the data that you are receiving you will be come a learning organization, possessing the attributes of knowledge and wisdom. A learning organization will be taught through experience or simply stated trial and error. Learning will maximize innovation, effectiveness, and performance, and this knowledge should be spread throughout the organization creating a very reliable, proven, and stable structure. From a personal perspective if your organizations structure is designed to support and manage information there should be no overload. There are endless consequences to information overload, especially when the overload is at the hands of social media technologies. Most of the technologies were designed with the expectations...
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...transition at the start of the bit if the data is a logic ‘0’ Note: Tanenbaum has a transition for a logic ‘1’ instead. 2. There is always a transition in the middle of the bit. 3. The direction of the transition is immaterial (hence there are two possible waveforms for any data stream depending upon the initial conditions). This gives us the following sample test data assuming pairs of logic levels for one actual bit: Data 1 1 0 0 1 0 1 1 Differential 01 10 10 10 01 01 10 01 Manchester (1) Differential 10 01 01 01 10 10 01 10 Manchester (2) After Halsall 2. Design Steps The output is toggling which suggests a flip flop. If Data = ‘0’ Output = Clock or inverse clock If Data = ‘1’ Output = 2 on –ve clock or inverse 2 on –ve clock Hence the output must be made up of two AND gates and an OR gate to select either * clock or inverse clock when Data = ‘0’ or * 2 on –ve clock or inverse 2 on –ve clock if Data = ‘1’ By De Morgan’s theorem (A.B)+(C.D) = (A.B).(C.D) So we can use three 2 input NAND gates instead of two 2 input AND gates and one 2 input OR gate. Finally we need to flesh out the additional circuitry required. 3. Test Data set The actual test data needs to be more along the following lines: Data 0 0 0 0 0 0 0 Output 10 10 10 10 10 10 10 01 01 01 01 01 01 01 Data 1 1 1 1 1 1 1 Output 01 10 01 10 01 10 01 10 01 10 01 10 01 10 Data 0 1 0 1 0 1 0 Output 10 01 01 10...
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...global sense. My objective is to benchmark industries with respect to the data shared between business partners and business to business transactions. The Food industry is not known as the leader in Customer – Vendor data sharing, so my research will first seek to define the leading industry and then define what characteristics separate the leaders. The secondary research will result in the following outputs. • Journal article summaries, with citations, of relevant information • Book chapters or segments that establish an academic foundations for the B to B interactions including relevant history and future expectations • A repository of my findings to share with my cohort 1. Research the current world class state-of-the-art in customer service. a. Define the world class quality reporting (WCQR) and service currently available i. By Industry segment ii. Include Depth of disclosure, delivery timing, iii. Business to Business commitment to achieve WCQR iv. Define WCQR Customer satisfaction and service levels v. Find, interview and evaluate the best companies, as possible ← Phase 2: Primary Data Collection – September to October 2010 Primary research will include Farmland Foods stakeholders and key Customer’s chosen to participate. Research will be conducted various methods that will be defined and changed to fit the environment as the data collection progresses. 1. Conduct an environmental scan within Farmland...
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...[pic] [pic] Data Loss and Misuse [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] Question: The service provider shall provide Client Based Data Leakage Services necessary to provide services and support for Data Loss Protection (DLP) with the following activities: a) Deploy the Clinet endpoint agent (XEA) to all new client machines. b) Deploy the XEA to at least 95% of existing in-scope client machines within 90 days of its initial release. c) Deploy any patches or updates to the XEA out to 95% of existing XEA-equipped machines (both clients and servers) within 45 days of those patches or updates being released from testing with approval to deploy. d) Monitor, investigate and remediate instances where the XEA ceases to function on any machine (client or server) that is still connecting to the XGI. e) Monitor, initiate investigation, and escalate alerts generated by the DLP system indicating mishandling of Clinet classified data. f) Distribute reports and data extracts as required. g) Support Tier I and II help-desk end-users’ and server application support questions arising from the XEA. Can you meet this requirement? Please explain below. ORGANIZATION understanding of Requirements: Clinet is looking for Client Based Data Leakage Services necessary to provide services and support for Data Loss Protection (DLP)...
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