data science in big data world the characteristics of big data are often referred to as the three vsvolume--how much data is therevariety--how diverse are different types of datavelocity--at what speed is new data generatedoften these characteristics are complemented with fourth vveracityhow accurate is the datathese four properties make big data different from the data found in traditional data management tools consequentlythe challenges they bring can be felt in almost every aspectdata capturecurationstoragesearchsharingtransferand visualization in additionbig data calls for specialized techniques to extract the insights data science is an evolutionary extension of statistics capable of dealing with the massive amounts of data produced today it adds methods from computer science to the repertoire of statistics in research note from laney and kartemerging role of the data scientist and the art of data sciencethe authors sifted through hundreds of job descriptions for data scientiststatisticianand bi (business intelligenceanalyst to detect the differences between those titles the main things that set data scientist apart from statistician are the ability to work with big data and experience in machine learningcomputingand algorithm building their tools tend to differ toowith data scientist job descriptions more frequently mentioning the ability to use hadooppigsparkrpythonand javaamong others don' worry if you feel intimidated by this listmost of these will be gradually introduced in this bookthough we'll focus on python python is great language for data science because it has many data science libraries availableand it' widely supported by specialized software for instancealmost every popular nosql database has python-specific api because of these features and the ability to prototype quickly with python while keeping acceptable performanceits influence is steadily growing in the data science world as the amount of data continues to grow and the need to leverage it becomes more importantevery data scientist will come across big data projects throughout their career benefits and uses of data science and big data data science and big data are used almost everywhere in both commercial and noncommercial settings the number of use cases is vastand the examples we'll provide throughout this book only scratch the surface of the possibilities commercial companies in almost every industry use data science and big data to gain insights into their customersprocessesstaffcompletionand products many companies use data science to offer customers better user experienceas well as to cross-sellup-selland personalize their offerings good example of this is google adsensewhich collects data from internet users so relevant commercial messages can be matched to the person browsing the internet maxpoint (