Characteristics of Big Data or the 3Vs/4Vs

In digital world, data are generated from various sourcesand the fast transition from digital technologies has led togrowth of big data. It provides evolutionary breakthroughs inmany fields with collection of large datasets. In general, itrefers to the collection of large and complex datasets whichare difficult to process using traditional database managementtools or data processing applications. These are availablein structured, semi-structured, and unstructured format inpetabytes and beyond. Formally, it is defined from 3Vs to 4Vs.3Vs refers to volume, velocity, and variety. Volume refers tothe huge amount of data that are being generated everydaywhereas velocity is the rate of growth and how fast the dataare gathered for being analysis. Variety provides informationabout the types of data such as structured, unstructured, semi-structured etc. The fourth V refers to veracity that includesavailability and accountability. The prime objective of big dataanalysis is to process data of high volume, velocity, variety, andveracity using various traditional and computational intelligenttechniques [1]. Some of these extraction methods for obtaininghelpful information was discussed by Gandomi and Haider[2]. The following Figure 1 refers to the definition of bigdata. However exact definition for big data is not defined andthere is a believe that it is problem specific. This will help usin obtaining enhanced decision making, insight discovery andoptimization while being innovative and cost-effective.It is expected that the growth of big data is estimated toreach 25 billion by 2015 [3]. From the perspective of theinformation and communication technology, big data is a ro-bust impetus to the next generation of information technologyindustries [4], which are broadly built on the third platform,mainly referring to big data, cloud computing, internet ofthings, and social business. Generally, Data warehouses havebeen used to manage the large dataset. In this case extractingthe precise knowledge from the available big data is a foremostissue. Most of the presented approaches in data mining are notusually able to handle the large datasets successfully. The keyproblem in the analysis of big data is the lack of coordinationbetween database systems as well as with analysis tools such asdata mining and statistical analysis. These challenges generallyarise when we wish to perform knowledge discovery and repre-sentation for its practical applications. A fundamental problemis how to quantitatively describe the essential characteristicsof big data. There is a need for epistemological implicationsin describing data revolution [5]. Additionally, the study oncomplexity theory of big data will help understand essentialcharacteristics and formation of complex patterns in big data,simplify its representation, gets better knowledge abstraction,and guide the design of computing models and algorithmson big data [4]. Much research was carried out by variousresearchers on big data and its trends [6], [7], [8].However, it is to be noted that all data available in theform of big data are not useful for analysis or decision makingprocess. Industry and academia are interested in disseminatingthe findings of big data. This paper focuses on challenges inbig data and its available techniques. Additionally, we stateopen research issues in big data. So, to elaborate this, thepaper is divided into following sections. Sections 2 dealswith challenges that arise during fine tuning of big data.Section 3 furnishes the open research issues that will helpus to process big data and extract useful knowledge from it.Section 4 provides an insight to big data tools and techniques.Conclusion remarks are provided in section 5 to summarizeoutcomes

Big data is usually composed of __________ V’s.

What are the three primary characteristics of Big Data, often referred to as the "Three Vs"?(1 Point)a) Volume, Value, Velocityb) Volume, Variety, Velocityc) Variety, Velocity, Validationd) Value, Velocity, Validation

Which of the following is NOT one of the 5Vs of Big Data?Question 18Answera.Visibilityb.Veracityc. Volumed.Variety

Which of the following attributes of big data incorporate data quality?VelocityVarietyVeracityVolume