4V of Big Data? Imagine all the information you alone generate each time you swipe your credit card‚ post to social media‚ drive your car‚ leave a voicemail‚ or visit a doctor. Now try to imagine your data combined with the data of all humans‚ corporations‚ and organizations in the world! From healthcare to social media‚ from business to the auto industry‚ humans are now creating more data than ever before. volume‚ velocity‚ variety‚ and veracity. Volume: Scale of Data Big data is big. It’s
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DATA COLLECTION Business Statistics Math 122a DLSU-D Source: Elementary Statistics (Reyes‚ Saren) Methods of Data Collection 1. 2. 3. 4. 5. DIRECT or INTERVIEW METHOD INDIRECT or QUESTIONNAIRE METHOD REGISTRATION METHOD OBSERVATION METHOD EXPERIMENT METHOD DIRECT or INTERVIEW Use at least two (2) persons – an INTERVIEWER & an INTERVIEWEE/S – exchanging information. Gives us precise & consistent information because clarifications can be made. Questions not fully understood by the respondent
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to : Data Flow Diagrams (DFDs) Data Flow Diagrams (DFDs) Data flow diagram (DFD) is a picture of the movement of data between external entities and the processes and data stores within a system Order CUSTOMER Status Message Status Data 2.0 Shipping Confirmation In-Stock Request WAREHOUSE 1.0 Shipping Order Check Status Order Data D1 Pending Orders 3.0 Issue Status Messages Order Data Payment Invoice Manage Accounts Receivable 5.0 Accounting Data Accounts Receivable Data 4.0
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WEEK 1 WHAT ARE DATA STRUCTURES? WHAT ARE ALGORITHMS? REVIEW OF JAVA AND OOP ENCAPSULATION‚ INHERITANCE‚ POLYMORPHISM CLASSES METHOD INTERFACES DATA STRUCTURES In computer science‚ a data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Different kinds of data structures are suited to different kinds of applications and some are highly specialized to certain tasks. For example‚ B-trees are particularly well-suited
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Systems Coursework Part 1: Big Data Student ID: 080010830 March 16‚ 2012 Word Count: 3887 Abstract Big data is one of the most vibrant topics among multiple industries‚ thus in this paper we have covered examples as well as current research that is being conducted in the field. This was done based on real applications that have to deal with big data on a daily basis together with a clear focus on their achievements and challenges. The results are very convincing that big data is a critical subject that
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UNCLASSIFIED UNCLASSIFIED 1 Open Data Strategy June 2012 UNCLASSIFIED UNCLASSIFIED 2 Contents Summary ................................................................................................... 3 Introduction ................................................................................................ 5 Information Principles for the UK Public Sector ......................................... 6 Big Data .......................................................................
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CHAPTER ONE INTRODUCTION 1.1 Background of the Study The significance of agriculture in bringing about economic growth and development of a nation cannot be underestimated‚ the reason why a nation possesses sustainable food security‚ is because it produces enough food to feed her citizens and even export these goods to other needy countries thereby generating foreign exchange which in turn increases the national income in the long-run. The agricultural sector serves all other sectors in the
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its simplest terms‚ the translation of data into a secret code. In order to read an encrypted file‚ the receiver of the file must obtain a secret key that will enable him to decrypt the file. A deeper look into cryptography‚ cryptanalysis‚ and the Data Encryption Standard (DES) will provide a better understanding of data encryption. Cryptographic Methods There are two standard methods of cryptography‚ asymmetric encryption and symmetric encryption. Data that is in its original form (unscrambled)
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Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus‚ data mining can be viewed as the result of
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trying to maximize its profits. A new‚ and important‚ tool in gaining this knowledge is Data Mining. Data Mining is a set of automated procedures used to find previously unknown patterns and relationships in data. These patterns and relationships‚ once extracted‚ can be used to make valid predictions about the behavior of the customer. Data Mining is generally used for four main tasks: (1) to improve the process of making new customers and retaining customers; (2) to reduce fraud; (3) to identify
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