Significance Of The Study Methodology Big Data Analytics

Development of data science has gone through three stages of birth data generated,a scientific data and big data. Three stages of the development changed also deepenedpeople see the world the concept of data. With the development of modern measuringtechnology and intelligent devices, in the form of data from the traditional singlestructured data evolution by structured data, semi-structured and unstructured data in theform of the composition of complex data. The rapid development of the Internet, mobileInternet platform for people to share this data, the resulting massive data beendiscovered and utilized, it creates a new concept of big data. Big Data analysis from thetechnical means using the latest data model, through the unique relationship between thedata produced a lot of associated and valuable conclusions.Big Data analysis in many areas has played a huge role. In business, the amount ofdata can be collected is enormous, whether direct consumer consumption data, or dailylife data can be collected, after the mass of collected data, correlation analysis, allowingmarketers to achieve precision marketing, increased turn over; in the sciences, such asmarine sciences, biological sciences, health sciences and astronomy, since the amount ofdata already accumulated history, coupled with advanced technology now generateddata, resulting in the amount of data is very huge, big data analytics scientists, may formthe data-intensive scientific discovery and a fourth paradigm in these massive data basis.In other areas can produce large amounts of data, large data analysis techniques canhave a greater effect.In theory, the big data technology and traditional data analysis techniques based onessentially the same. Traditional data analysis techniques has drawbacks, large data alsomay have. Especially in terms of data sources and data integrity, the limitations of largedata analysis techniques are very obvious. Because the vast amounts of data and can notguarantee that every data each other is true and reliable, and the so-called mass dataonly relatively large number, not all of the data concerned. Therefore, the conclusionobtained by the analysis of large data may have a larger more practical value, but it isnot necessarily true. And big data analysis of the relevant populations may cause somedegree of privacy infringement. Thus, in the application of Big Data technologiesshould be scientific and rational, not abuse.