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What is Data Analysis

Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture
It is a process of inspecting, refining, transforming, and modeling data with the aim of extracting useful information, deducing conclusions, and enabling decision-making.
Published in Chapter:
Disease Monitoring of Cucumber in Polyhouse Through IoT-Based Mobile Application
Hemalatha R. (Sri Sivasubramaniya Nadar College of Engineering, India), Radha S. (Sri Sivasubramaniya Nadar College of Engineering, India), and Muthumeenakshi K. (Sri Sivasubramaniya Nadar College of Engineering, India)
DOI: 10.4018/978-1-7998-1722-2.ch017
Abstract
Most countries have an economy that is dependent on agriculture—either in a magnificent or small way, from employment generation to national income contribution—implying that agriculture is inevitable. Polyhouse farming is a new and widely accepted method of farming in the present days. The polyhouse is made in such a way that it can provide water and fertilizers in required amounts in a controlled manner, which can result in high yields. Polyhouse requires severe monitoring of crops as stagnant air, and lack of air circulation will lead to breeding of insects and materialistic loss. Hence, this chapter proposes an IoT-based disease-monitoring prototype for an agricultural/polyhouse application. The prototype is designed and tested to identify the disease onset in cucumbers. This work initially focuses on recognizing the critical cucumber diseases in polyhouse using NodeMCU and Raspberry-Pi-based hardware model. The decisions to be made and the major changes in the sensed parameters if any will be intimated to the farmers using a specifically designed mobile application.
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Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights
Evaluating data with analytical and logical perceptive to survey each element of the data.
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Internet of Things and Big Data-Driven Data Analysis Services for Third Parties: Business Models, New Ventures, and Potential Horizons
A process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
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The Big Data Era: Data Management Novelties for Visualizing, Exploring, and Processing Big Data
Systematic processing of large datasets, often in real or near-real time, and their presentation in ways that can support the decision-making process.
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E-Learning Applications through Space Observations
The process of systematically applying statistical and logical techniques to describe, summarize, and compare data; it is the process by which the data requirements of a functional area are identified, element by element. Each data element is defined from a business sense, its ownership is identified, and users and sources of that data are identified. These data elements are grouped into records, and a data structure is created which indicates the data dependencies.
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Data Analysis on Global Stratification
Data Analysis is a process of gathering and extracting information from the data already present in different ways and order to study the pattern occurs.
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Input Analysis for Stochastic Simulations
The process of inspecting, cleaning, transforming, and modeling data with the goal of extracting useful information.
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Accelerating the Digitalization of the Supply Chain: An Empirical Research About COVID-19 Crisis
Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.
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Big Data, Who Are You?
This is a class of statistical methods that make it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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Information Technology Act 2000 and the Potential Use of Data Analytics in Reducing Cybercrime in India
The process of collecting, organizing any data in proper order is comes under the data analysis. In analytical and logical reasoning to gain information these data analysis used.
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Systems and Control Theory for Medical Systems Biology
The analysis of time course data from a system in order to understand the nature of the signal generating mechanisms associated with a system. These are often unwanted noise or errors in the process and are used to modify or correct the mathematical model.
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Statistical Techniques for Research
It is a set of techniques that allow us to examine a data set with the aim of obtaining a set of conclusions that can facilitate later decision-making.
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Urban Energy Efficiency Assessment Using Stochastic and Deterministic Data Analysis: A Proposed Sustainable Urban Energy Assessment
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Data Analysis and Integration in Healthcare
A systematic use of data to drive fact-based decision making for measurement, planning, learning, and management.
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How to Encourage Reflective Practice With the Help of Collaborative Video Annotation: Social Video Learning in Teacher Education
A process of dealing with data with the main objective to discover useful information, support decision-making processes, and draw conclusions.
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First of All, Understand Data Analytics Context and Changes
This is a class of statistical methods that make it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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Survey Forms for Data Collection: Key Considerations
This is the process of gathering and organizing data to allow for the formulation of meaningful and relevant conclusions.
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Artificial Intelligence and Machine Learning in Higher Education
This is the analysis of learner data to make the best use of time and see student outcomes before it occurs to avoid adverse consequences.
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A Generalized Overview of the Biomedical Image Processing From the Big Data Perspective
Data analysis is the collection of data processing techniques to extract meaningful information, which is beneficial to support different decision-making tasks.
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Transformation of the Dissertation: From an End-of-Program Destination to a Program-Embedded Process
The process and techniques for transforming and evaluating information using qualitative or quantitative tools to discover findings or inform conclusions.
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Strategic Approach to Business Intelligence and Its Impacts on Organizational Performance
As a result of data analysis, cleaning, transformation and modeling, It is an important process that supports obtaining useful information, making information and making decisions.
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Plan and Rules for Data Analysis Success: A Roadmap
This is a class, of statistical methods, that makes it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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An Evolving System in the Text Classification Problem
It is an activity which works on collected data sets to search for patterns, trends, relationships or any kind of useful information.
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Exploratory Data Analysis on Breast Cancer Prognosis
The process of systematically applying statistical and/or logical techniques to describe and evaluate data.
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Big Data Analytics Lifecycle
Data analysis is the systematic examination, manipulation, and modelling of data in order to uncover valuable insights, propose valid conclusions, and facilitate informed decision-making. This process entails the utilization of analytical and statistical methodologies and algorithms to analyse and assess data.
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The Role of Information Professionals in South Africa in the Provision of Information During COVID-19
It is the process of inspecting, cleansing, transforming and modelling data to discover useful information, informing conclusions and supporting decision- making.
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K-Nearest Neighbors Algorithm (KNN): An Approach to Detect Illicit Transaction in the Bitcoin Network
Is a family of statistical methods whose main characteristics are that they are multidimensional and descriptive.
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Big Data Visualization: KPI Dashboards for Big Data Visualization
the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.
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A Renewable Energy Assessment Method by Parametric and Non-Parametric Models' Data Analysis
The process that collects raw data and turns it into meaningful and useful information using statistical methods.
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Investigating the Factors for Predictive Marketing Implementation in Algerian Organizations
This is a class of statistical methods that makes it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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Designing Medical Research Web Sites
Related to a website, data analysis involves the interpretation of logged data maintained generally for a website and specifically related to the needs of researchers.
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Motives and Methods for Quantitative FLOSS Research
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Big Data Analysis in IoT
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Innovative Formalism for Biological Data Analysis
A process of inspecting, adapting, and modeling data with the goal of discovering useful information and decision making.
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Evaluation of Strategic Opportunities and Resulting Business Models for SMEs: Employing IoT in Their Data-Driven Ecosystems
A process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
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Demand Forecasting Models With Time Series and Random Forest
Examining data for to extract information with the help of a set of computational methods or techniques that range from basic descriptive statistical techniques to more sophisticated data mining.
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From the Data to the Statistical Analysis of Football: The Case of the Italian Serie A League
It is a process of collecting, transforming, and modeling data to highlight information that suggests conclusions and supports decisions.
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Big Data Applications in Business
This is a class of statistical methods that make it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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Building an Analytics Culture to Boost a Data-Driven Entrepreneur's Business Model
This is a class of statistical methods that make it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.
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Web 2.0 Mash-Up System for Real Time Data Visualisation and Analysis Using OSS
Data analysis is a process, where data is parsed and filtered through systematic procedures and methods to get useful information which helps in decision making and helping with possible conclusions.
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Learning Analytics for Smart Classrooms
Statistical analysis methods for analyzing large amounts of information.
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Collective Case Study: Making Qualitative Data More Impactful
The process of breaking down units into individual pieces for comparative and contrasting analysis, seeking intersection between pieces to identify patterns, and examining outliers to best understand how the pieces work in aggregate to explain the whole.
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Research Methodologies Used in Library and Information Studies Masters' Degree Dissertations at the University of Botswana
This refers to the act of making sense out of the raw collected data from research, for purposes of resolving the research problem. Without data analysis, the data collected will remain data, and will not make sense and thus not provide answers to the research question.
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