slide 1: Intersection of
Big Data and
Cloud
Computing
slide 2: Intersection of Big Data and Cloud Computing
The entire industry is moving around SMAC Social-Mobile-
Analytics-CloudandIOTtechnologies.Thisiswheremostof
the opportunities lie for the next couple of years for both
whowanttogetintoITfieldandforthosewhoarenectdeep
into the IT. These technologies don ’t work alone but they
workintandemwitheachother.Inthisblogwewillexplore
how the Big Data and Cloud technologies go hand in hand.
Having a good grip on the Big Data and the Cloud
technologieswillincreasethe candida t e’sprospects.
slide 3: Traditionally data used to be stored on high end machines with proprietary software
both of which are expensive to procure and maintain. Trend is moving towards the Big
Data tools and technologies where we use commodity machines and open source
s oftw ar e’s.
The open sources softwares are relatively cheaper when compared to the proprietary
softwares and can be customized the way we want to as per our requirements. Apache
Hadoop Hive Pig Sqoop Oozie are a few of the popular open source Big Data
softwares.Thecodeforthemcanbegothere.
The different companies like Cloudera Hortonworks
MapR Databricks DataStax take the open source
software from the Apache Software Foundation and
fine tune them make them much more user friendly
and offer it as a product with commercial support
documentationtrainingsetc.
slide 4: Comingtothecommodityhardwarethesemachinesarenotaspowerfulasservergrade
machines and not as dumb as desktop grade machines they fall in between. Big Data
processinghappensonthousandsofthesecommoditymachines.Themorethedatathe
morethemachinesrequired.
When the machines are in thousands there is a good probability that some of the
machines go down on a regular basis. Instead of using the proprietary and high-end
hardwaretoaddressthefailurescenariosthesoftwarewilltacklethem.
The hardware failures can be like a hard disk going down a problem with the network
card or it can be any one of the infinite number of problems. In this case the software
willautomaticallyroutethedataandtheprocessingtoahealthymachine.
slide 5: With the amount the different types/complexity of the data increasing day by day
increasingly more machines are required for the storage and computation. Now a days
the processing is also being shifting to specialized hardware like the GPUs from Nvidia
ASIC processors like the Tensor Processing Unit from Google. These specialized
hardwaresnotonlyareexpensivebutgetoutdatedfast.
ThisiswhereCloudcomesintheplay.IntheCloudthehardwarecanbegotwithoutany
upfront commitment and we exactly pay for what we use. It ’s exactly like renting a car.
L et’ssay a serverintheAmazon Cloudcosts 1andhour.If we useit for10 hoursthen
weneedtopay10toAmazonattheendofthebillingcycle.
The different Cloud vendors provide services like Amazon Elastic MapReduce Google
CloudDataprocwhich makesit easy tospawnaclusterofmachinesanddocomplicated
BigDataprocessingusingSparkHivePigandotherBigDatasoftwares.
slide 6: As a user we d o n ’t need to worry about procuring thehardware installing the software
and other minute details. We can simply think more about the business and the
customers let the Cloud vendor worry about the rest of the details. The different
servicesprovidedbytheAmazonandtheGoogleCloudarementionedhere.
To summarize Cloud and Big Data technologies have very good prospects but an
individual with the combination of these two technologies will make him/her much
moredesirableintheITfield.
Turn to our expert trainers and career advisors who will make comfortable with Cloud
ComputingwithAWSandBigDatatrainingprogram.
ForinformationonKovidAcademytrainingprogrammesclickhere.
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