Introduction to Data Visualization Definition of Data Visualization Terms related to Data Visualization Data Mining Data Recovery Data Redundancy Data

Download Introduction to Data Visualization Definition of Data Visualization Terms related to Data Visualization Data Mining Data Recovery Data Redundancy Data

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Lecture 31

Lecture 31Introduction to Data VisualizationDefinition of Data VisualizationTerms related to Data VisualizationData MiningData RecoveryData RedundancyData AcquisitionData ValidationData IntegrityData VerificationData Aggregation

Continued.Data mininganalytic process designed to explore dataanalyzing data from different perspectivessummarizing it into useful informationData recoveryhandling the data through the data from damaged, failed, corrupted, or inaccessible secondary storage mediarecovery required due to physical damage to the storage device or logical damage to the file system

Continued.Data redundancyadditional to the actual datapermits correction of errors Data acquisitionprocess of sampling signalsmeasure real world physical conditionsconverting the resulting samples into digital numeric valuesData validationprocess of ensuring that a program operates on clean, correct and useful data

Continued.Data integritymaintaining and assuring the accuracy and consistency of dataensure data is recorded exactly as intendedData verificationdifferent types of data are checked for accuracy and inconsistencies after data migration is doneData aggregationinformation is gathered and expressed in a summary formto get more information about particular groups

Continued.Need for data visualizationImportance of data visualizationLimitation of spreadsheet Interpretation through data visualizationidentify areas that need attention or improvementunderstand what factors influence design systempredict how to change system design accordinglypredict the efficiency of systemInteractive VisualizationHumans interact with computers to create graphic illustrations of informationProcess can be made more efficientHuman inputResponse time

Continued.Combination of disciplinesdata visualization to provide a meaningful solution requires insights from diverse fields like statistics, data mining, graphic design, and information visualizationsoftware-based information visualization adds building blocks for interacting with and representing various kinds of abstract data Continued.Process of data visualizationAcquireParseFilterMineRepresentRefineInteract

AcquireObtain the data, whether from a file on a disk or a source over a networkParseProvide some structure for the datas meaning, and order it into categoriesFilterRemove all but the data of interestMineApply methods from statistics or data mining as a way to discern patterns or place the data in mathematical contextRepresentChoose a basic visual model, such as a bar graph, list, or tree.RefineImprove the basic representation to make it clearer and more visually engaging.InteractAdd methods for manipulating the data or controlling what features are visible.Continued.Iteration and Combination of steps of data visualizationUnique requirements for each projecteach data set is differentthe point of visualization is to expose that fascinating aspect of the data and make it self-evidentreadily available representation toolkits are useful starting pointsthey must be customized during an in-depth study of the task

Continued.Avoid usage of excess dataAudience of problemQuantitative messagesTime-SeriesRankingPart-to-WholeDeviationFrequency-DistributionCorrelationNominal ComparisonGeographic or Geospatial

Time-series: A single variable is captured over a period of time, such as the unemployment rate over a 10-year period. A line chart may be used to demonstrate the trend

Ranking: Categorical subdivisions are ranked in ascending or descending order, such as a ranking of sales performance by sales persons during a single period A bar chart may be used to show the comparison across the sales personsPart-to-whole: Categorical subdivisions are measured as a ratio to the whole A pie chart or bar chart can show the comparison of ratios, such as the market share represented by competitors in a marketDeviation:Categorical subdivisions are compared again a reference, such as a comparison of actual vs. budget expenses for several departments of a business for a given time periodA bar chart can show comparison of the actual versus the reference amountFrequency distribution: Shows the number of observations of a particular variable for given interval, such as the number of years in which the stock market return is between intervals such as 0-10%, 11-20%, etc.A histogram, a type of bar chart, may be used for this analysisA boxplot helps visualize key statistics about the distribution, such as mean, median, quartiles, etc.Correlation:Comparison between observations represented by two variables (X,Y) to determine if they tend to move in the same or opposite directions For example, plotting unemployment (X) and inflation (Y) for a sample of months. A scatter plot is typically used for this messageNominal comparison: Comparing categorical subdivisions in no particular order, such as the sales volume by product codeA bar chart may be used for this comparison

Geographic or geospatial: Comparison of a variable across a map or layout, such as the unemployment rate by state or the number of persons on the various floors of a buildingA cartogram is a typical graphic usedContinued.Characteristics of effective graphical displayshow the dataavoid distorting what the data have to saypresent many numbers in a small spacemake large data sets coherentencourage the eye to compare different pieces of datareveal the data at several levels of detail, from a broad overview to the fine structureserve a reasonably clear purpose: description, exploration, tabulation or decorationbe closely integrated with the statistical and verbal descriptions of a data set

Continued.Visual perception and data visualizationEffective graphics take advantage of pre-attentive processing and attributes and the relative strength of these attributesTypes of information displayTablesGraphs Data display requires planningData collection

Benefits of data visualizationVisualization is so powerful and effective that it can change someones mind in a flashit encompasses various dataset quickly, effectively and efficiently and makes it accessible to the interested viewersIt motivates us to a deep insight with quick access It gives us opportunity to approach huge data and makes it easily comprehensible, be it the field of entertainment, current affairs, financial issues or political affairsIt also builds in us a deep insight, prompting us to take a good decision and an immediate action if neededIt has emerged in the business world lately as geospatial visualizationThe popularity of geo-spatial visualization has occurred due to lot of websites providing web services, attracting visitors interest

Data Visualization with C++Chapter 1 Arrays, Pointers and StructuresChapter 2 Objects and ClassesChapter 4 InheritanceChapter 6 Algorithm Analysis

Chapter 1"Arrays, Pointers and Structures"In this chapter we examined the basics of pointers, arrays, and structuresThe pointer variable emulates the real-life indirect answer. In C++ it is an object that stores the address where some other data reside. The pointer is special because it can be dereferenced, thus allowing access to those other dataThe NULL pointer holds the constant 0, indicating that it is not currently pointing at valid dataA reference parameter is an alias. It is like a pointer constant, except that the compiler implicitly dereferences it on every accessReference variables allow three forms of parameter passing: call by value, call by reference, and call by constant referenceChoosing the best form for a particular application is an important part of the design processContinued.An array is a collection of identically typed objectsIn C++ there is a primitive version with second-class semantics A vector is also part of the standard libraryIn both cases, no index range checking is performed, and out-of-bounds array accesses can corrupt other objects. Because primitive arrays are second-class, they cannot be copied by using the assignment operatorInstead they must be copied element by element; however, a vector can be copied in a single assignment statementA vector can be expanded as needed by calling resizeContinued.Structures are also used to store several objects, but unlike arrays, the objects need not be identically typedEach object in the structure is a member, and is accessed by the . member operatorThe -> operator is used to access a member of a structure that is accessed indirectly through a pointerWe also noted that a list of items can be stored non-contiguously by using a linked listThe advantage is that less space is used for large objects than in the array-doubling techniqueThe penalty is that access of the ith item is no longer constant-time but requires examination of i structuresChapter 2 Objects and Classes"In this chapter we described the C++ class constructThe class is the C++ mechanism used to create new types. Through it we candefine construction and destruction of objects,define copy semantics,define input and output operations,overload almost all operators,define implicit and explicit type conversion operations (sometimes a bad thing)provide for information hiding and atomicityThe class consists of two parts: the interface and the implementationThe interface tells the user of the class what the class does. The implementation does itThe implementation frequently contains proprietary code and in some cases is distributed only in precompiled formContinued.Information hiding can be enforced by using the private section in the interfaceInitialization of objects is controlled by the constructor functions, and the destructor function is called when an object goes out of scopeThe destructor typically performs clean up work, closing files and freeing memoryFinally, when implementing a class, the use of const and correct parameter passing mechanisms, as well as the decision