How is Big Data Different from Data Science?

1. HowisBigDataDifferentfromDataScience? DataSciencehasbeenmaking wavesever sincedigitizationanddisruptive technologieswere evolved.Sohasbeen Big Data.In fact, Bigdatahasbeen makingnoiseevenbeforedatasciencecameintobeing,orisit? Butwhat arethey? Howdoyou defineDataScienceandwhatdoesBigDatamean? Canweusetheminterchangeablyor aretheytwodifferentidentities?Keep reading to knowmore.But before do thedetailed comparison between thetwo, let’s have a look at the individual terms, their definition and is there any relation betweenthetwo. DataScience&BigData–theDefinitions,Comparison,&theRelation! According to the definition data scienceisnothing but afield of study, which blends programming skills, domain expertise, and in-depth knowledge of statistics and mathematics that helps you to deduct meaningful insights from the available data. In another words, data science is a domain that not only includes but also involves working with a humongous chunk of data and useitfor building both predictive and prescriptive models along with prescriptive analytical models. Data Science is all about building a model, validating it and using the right data to deploy the best modelcreated. Data Science professionals apply numbers, images, videos, text, audio and most importantly machine learning algorithms to produce AI-based systems for the tasks that would usually require human intelligence. Result: Valuable insights, which businessleadersandanalystscantranslateintobusinessvaluesthataretangible. On the other hand – Big Data is nothing but a data set that is not only huge in volume but also exponentially growing with time. Big Data refers to the data sets that are not only large but are also complex in nature, which can’t be stored or processed using the traditional data management tools. Big data comprises huge amount of information that is volume; speed at which this data is being generated that is ‘velocity;’ scope of the data points that are covered that is ‘variety;’ and togetherthisisknownasBigData’s‘ThreeVs.’

2. In another words, Big Data is nothing but the voluminous data or you can say it is theinformation or even therelevant statistics,which the businessesacrossthe globeacquiretofindsolutionsfortheirbusinessproblems.BigDataishuge enough to be processed using the traditional methodshence there are different softwareandtoolstocreateandpreparebigdata. Big data helps in discovering trends, patterns, thus helpsin making decisions that arecloselyrelatedtobothhumanbehavioraswellasinteractiontechnology. Now that we know what each of the term individually means and stands let’s see howeachofthemfair againsteachother.

3. After comparing the two,you will see that both data science and big data are related. In simple words, data science is an umbrella term, which encompasses entire tools andtechniquesthatareusedduringthelifecyclestagesofthedatawhichisuseful. In comparison, Big Data is nothing but huge data sets, which need specialized and most often than not innovative techniques as well as technologiesfor an efficient use ofavailabledata. DataScienceTrendsin2021 While data science was being written off in 2020, there has been a different wave thisyear. According to the experts, data provenance will gain prominence. As per theexperts,theindustryhasnotyettaken the dataprovenanceassessment as seriously. Citing some of thebad exampleswhere the useof someunchecked data that has ledtomorediscriminationandmisinformation. The latest trend in Data Science usage has been the applications of Generative Adversarial Networks aka GANs. For instance, the Deepfake of the British queen Elizabethhad stirredthemassesandthereweremixedreactions tothevideo. However,thepurposeofthevideowastobringthe‘trust’factorinthediscussion.

4. There will be varied uses of data science in the coming years, asexperts predict. And aspiring professionals in data science field will need to constantly upskill or reskilltheirdatascienceskillstostayrelevantintheindustry. • WhyIndustryChoosesDataScienceOverBigData • There isno debate about which is better, however, industries; organization; and even businesses choose Data Science professionals over Big Data professionals becausedatasciencemakesdatabetter. • DataScienceismoreversatileascomparedtoBigData. • DataScienceisalwaysevolvingwhile Big Data will continuetogrow, however,itwillbedatasciencethatwillgivethatdatasomemeaning. • Data Science skills are continuously evolving whereas Big Data still uses old skills. • While Big Data is growing by leaps and bounds, so is Data Science evolving at a faster pace andwill continuetodo so. Reason: Businessesare becoming data driven and innovative, and to keep up with the tremendous growth, organizations needprofessionalswithlatestdatascienceskills. • Are you ready to become the most sought-after data science professional? The path tosuccessiskeepupskilling,reskilling,andupgradingyourknowledge.