Data Essays

  • Data Analysis: Big Data

    1165 Words  | 5 Pages

    Abstract The volume of data generated by different organisations has increased consistently in the past few years. Hence, it is necessary to analyse this voluminous data to produce profitable results. This paper presents a way of analysing merchant datasets using the confusion matrix concept to attain the maximum precision, recall and accuracy for the given merchants. Moreover, various python libraries have led to a better automation tool algorithm for analysis. Introduction Data Analytics[1] is the

  • The Importance Of Big Data

    908 Words  | 4 Pages

    Signal processing and machine learning have been two of the most used and matured fields of data science. They are highly interdisciplinary fields building upon ideas from many different kinds of fields such as artificial intelligence, optimization theory, information theory, statistics, control theory, and many other disciplines of science, engineering, and mathematics. Because of their implementation in a wide range of applications, machine learning has covered almost every scientific domain, which

  • Primary Data Methodology

    2677 Words  | 11 Pages

    Methodology: Primary Data vs Secondary Data. Based on review, the researcher practiced most on the secondary data where he collected the information from the previous books, journals, articles, news and internet. Ths can be see through the books of Mintzberg and Waters (serial book and journal from 1972 – 1986), Brunet, J.P.H. Mintzberg and J. Waters: ‘Does planning impede strategic thinking?’, Chandler, A. D.: Strategy and Structure, MIT Press, Cambridge, 1962. and many others. The researcher do

  • The Importance Of Data Cleaning

    2111 Words  | 9 Pages

    code, clean and edit the data. Computers play a major role in different phases of research starting from conceptual, design and planning, data collection, data analysis and research publication phases. The main objective of data display is to summarize the characteristics of a data and to make the data more comprehensible and meaningful. Usually data is presented depending upon the type of data in different tables and graphs. This will enables not only understand the data behaviour, but also useful

  • Outlier In Data Mining

    1811 Words  | 8 Pages

    1.1 Introduction Today in Dataset there exist data objects that do not comply with the general behavior or model of the data. Such data objects which are heavy different from or inconsistent with the remaining set of data, are called outliers. An outlier is a data set which is different from the remaining data. Outlier is also denoted to as deformity, deviants or anomalies in the data mining and statistics literature. In most applications the data is produced by one or more generating processes

  • Data Reduction Issues In Data Integration

    1405 Words  | 6 Pages

    issue in data integration is redundancy. If an attribute is derived from another attribute it may be redundant. To detect redundancies you can use the correlation analysis, this method will detect inconsistencies in the resulting dataset. 3.2 Entity Identification Problem There a number of issues during data integration. Two issues can be tricky which include schema integration and also object matching. Entity identification problem derives from how can real world entities from multiple data sources

  • Data Center Importance

    913 Words  | 4 Pages

    difficult as the business grows and the availability of data might not always be there. That is why data centres are important, data centres provide remote storage which means less stress on having to store data in house and cheaper than buying your own hardware/software. Data processing is made easier since there is personnel working around the clock to insure that data is accessed and stored. Scalability of services is made simple because data centres have tones of storage space can always adjust

  • Big Data Methodology

    772 Words  | 4 Pages

    Methodology for Big Data Security Authors: Ramya.P E-mail: Manjula.R Karthikeyan.S Abstract There has been an increasing interest in big data and big data security with the expansion of network technology and cloud computing. However, big data is not an entirely new technology but an lean-to data mining. In this paper, we describe the background of big data, data mining and big data features, and suggest attribute selection methodology for big data for shielding the

  • The Importance Of Data Science

    10910 Words  | 44 Pages

    To put away Data Science in a simple sentence: It is the study of where information comes from, what it represents and how it can be turned into a valuable source in the establishment of business and IT approaches. In the last decade, Data Science has silently grown to include businesses and organizations world-wide. It is now being used by governments for research and analytics, geneticists, astronomers, engineers as well as for the entrepreneurs. Technically, this includes robotics, machine translation

  • Unstructured Data Case Study

    10155 Words  | 41 Pages

    CHAPTER - I INTRODUCTION 1.1 What is Unstructured Data? Unstructured data is a generic label for describing data that is not contained in a database or some other type of data structure . Unstructured data can be textual or non-textual. Textual unstructured data is generated in media like email messages, PowerPoint presentations, Word documents, collaboration software and instant messages. Non-textual unstructured data is generated in media like JPEG images, MP3 audio files and Flash video files

  • Advantages And Disadvantages Of Data Science

    1464 Words  | 6 Pages

    DATA SCIENCE: Data science means mining of structured and unstructured amount of data into a finite form or to identify pattern which help an organization to decrease it costs, increase it efficiency and also to gain new market opportunities. Many of the industries are hiring new data scientists for converting the given raw data into useful information which benefits the organization which is an advantage for them in terms of increasing their competition in this modern world. Data science is a study

  • Importance Of Big Data

    1490 Words  | 6 Pages

    Introduction Big data is defined as large quantity of data which have need of new technologies and architecture to make possible to extort value from it by capturing and analysis process. New sources of big data include location specific data which has arrived from traffic management and from the tracking of personal devices such as Smartphone’s [1]. Big data has come into view because we are living in the world which makes mounting use of data intensive technologies. Due to such large size of data it becomes

  • Advantages Of Big Data Usage

    1314 Words  | 6 Pages

    Big Data Usage in terms of market recruitment. Possibilities and limitations. “Big Data” is gaining popularity rapidly. A number of monthly “Big Data” requests in Yandex (region - the whole world, metric Yandex Wordfast) from March 2015 till February 2017 have increased from 6 536 to 12 840. For example IBM company has launched free online course on big data. Moscow Government carries out town projects not only taking into consideration big data but also uses is to forecast efficiency of town

  • A Short Summary: Big Data Vs. Data Mining

    1007 Words  | 5 Pages

    Big Data vs Data Mining 1. Introduction What is Big Data? Big Data refers to huge volume of data that can be structured, semi-structured and unstructured. It comprises of 5 Vs i.e. a. Volume: It refers to amount of data or size of data that can be in quintillion when comes to big data. b. Variety: It refers to different types of data like social media, web server logs etc. c. Velocity: It refers to how fast data is growing, data is exponentially growing and at a very fast rate. d. Veracity: It

  • Advantages Of Data Analytics

    3340 Words  | 14 Pages

    and data mining to discover scalable computational methods for finding useful models from massive amounts of data. Analytics is the discovery and communication of meaningful patterns in data. These models can be used in a variety of tasks, including clustering/discovery, regression/prediction, and classification/ranking. Data Analytics building predictive models and discovering patterns from data. 16.4 Data Analytics: Concept and Process Firms may commonly apply analytics to business data, to

  • Examples Of Negative Data Mining

    2396 Words  | 10 Pages

    Head of the CSE Dept CBIT HYDERABAD CBIT HYDERABAD ABSTRACT Data mining is a technique of extracting knowledge from Enormous amount of data.To generate frequent item sets Apriori Algorithm is used. From these frequent item sets we generate rules. Rules which satisfy minimum confidence are called as Association rules

  • Three Characteristics Of Data Communication

    712 Words  | 3 Pages

    commonly called as data communication. Electronic communication basically comprises of telecommunication and data communications. The use of electronic media like telephone, telegraph, or television to transmit information, either directly or via computer is often referred as Telecommunication. On the other hand, data communication basically is concentrated in the transfer of data or information between computers devices. Data communication is the active process of transporting data from one point to

  • Importance Of Data Analytics

    763 Words  | 4 Pages

    DATA ANALYTICS In the world of technology growing at lightning speed data plays an important role in all runs of life. Be it a grocery shop or a multinational company, everywhere data is a game changer and helping everyone grow exponentially. So, the question arises what exactly is data analytics? Data is any piece of information that is collected and is used for referencing and analyzing. Analytics on the other hand provides definite figures with the help of mathematics, statistics and prognostic

  • Outliers In Data Mining

    784 Words  | 4 Pages

    Abstract- Outlier detection is an active area for research in data set mining community. Finding outliers from a collection of patterns is a very well-known problem in data mining. Outlier Detection as a branch of data mining has many applications in data stream analysis and requires more attention. An outlier is a pattern which is dissimilar with respect to the rest of the patterns in the data set. Detecting outliers and analyzing large data sets can lead to discovery of unexpected knowledge in area

  • Importance Of Data Mining

    990 Words  | 4 Pages

    DATA MINING IN INSTITUTIONAL DEDUCTION DATA MINING: Data mining is a process of analyzing data from different perspectives and summarizing it into useful information. Data are any facts, numbers, text that can be processed by a computer. The patterns, associations, or relationships among all collected data can provide information. Information can be converted into knowledge about historical patterns and future trends. To maximize user access and