billion bytes of data in digital form be it on social media‚ blogs‚ purchase transaction record‚ purchasing pattern of middle class families‚ amount of waste generated in a city‚ no. of road accidents on a particular highways‚ data generated by meteorological department etc. This huge size of data generated is known as big data. Generally managers use data to arrive at decision. Marketers use data analytics to determine customer preferences and their purchasing pattern. Big data has tremendous potential
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this 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. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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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
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1) ________ is data that has been organized or presented in a meaningful fashion. 1) _______ A) A number B) Information C) A symbol D) A character 2) Which of the following is NOT one of the four major data-processing functions of a computer? 2) _______ A) storing the data or information B) gathering data C) analyzing the data or information D) processing data into information
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Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or
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project. In primary data collection‚ we collect the data ourselves by using methods such as interviews and questionnaires. The key point here is that the data we collect is unique to us and our research and‚ until we publish‚ no one else has access to it. There are many methods of collecting primary data and the main methods include: • QUESTIONNAIRES • INTERVIEWS • FOCUS GROUP INTERVIEWS • SURVYES • OBSERVATION • DIARIES • ANALYSING THE DATA The primary data‚ which is generated by
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COURSE NO | SUBJECT | FACULTY | CC09 | FINANCIAL MANAGEMEMENT | Ms. AMBILI JOSE | CC10 | MARKETING MANAGEMENT | Mr. SREENATH .R | CC11 | HUMAN RESOURCE MANAGEMENT | Dr. ANU GEORGE | CC12 | OPERATIONS MANAGEMENT | Mr. NIBU RAJ ABRAHAM | CC13 | ENVIRONMENT MANAGEMENT | Mr. GIJO GEORGE | CC14 | OPERATIONS RESEARCH | Ms. AMBILI JOSE | CC15 | RESEARCH METHODOLOGY | Mr. JEFFIN JOHN | CC16 | MANAGEMENT INFORMATION SYSTEMS | Mr. MIDHUN JOSE | CC17 | VIVA- VOCE | | CC09 -FINANCIAL
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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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The Difference Between Data Centers and Computer Rooms By Peter Sacco Experts for Your Always Available Data Center White Paper #1 EXECUTIVE SUMMARY The differences between a data center and a computer room are often misunderstood. Furthermore‚ the terms used to describe the location where companies provide a secure‚ power protected‚ and environmentally controlled space are often used inappropriately. This paper provides a basis for understanding the differences between these locations
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CD only provides the total number of reading‚ it is not able to track the number of reading in the individual month. In order to know the engagement rate after Feb 4‚ it can only track the percentage change after Feb 4. Therefore‚ use total number of reading subtracts the number of reading during Jan 22 – Feb 4‚ and then we can get the number of reading after that period. (Eg. The total number of reading is2928 and reply is 63; 2928-1099=1829; 63-33= 30). Why drop? The application season for
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