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  • - Cloud is a, it's a godsend for data scientists.

  • Primarily because you're able to take the,

  • or you take your data, take your information

  • and put it in the cloud,

  • put it in the central storage system.

  • It allows you to bypass the physical limitations

  • of the computers and the systems you're using

  • and it allows you to deploy the analytics

  • and storage capacities of advanced machines

  • that do not necessarily have to be your machine

  • or your company's machine.

  • Cloud allows you not just to store large amounts of data

  • on servers somewhere in California or in Nevada,

  • but it also allows you to deploy very advanced

  • computing algorithms and the ability to do

  • high performance computing

  • using machines that are not yours.

  • So, think of it as you have some information,

  • you can't store it, so you send it to storage space,

  • let's call it cloud, and the algorithms that you need to use

  • you don't have them with you, but then on the cloud

  • you have those algorithms available.

  • So, what you do, is you deploy those algorithms

  • on very large data sets and you're able to do it

  • even though your own systems, your own machines,

  • your own computing environments

  • were not allowing you to do so.

  • So, cloud is beautiful.

  • And, the other thing that cloud is beautiful for

  • is that it allows multiple entities

  • to work with same data at the same time.

  • So, you can be working with the same data

  • that your colleagues in, say, Germany,

  • and another team in India, and another team in Ghana,

  • they are collectively working

  • and they are able to do so because the information

  • and the algorithms and the tools and the answers

  • and the results, whatever they needed

  • is available at a central place.

  • Which we call cloud, so cloud is beautiful.

  • At the Big Data University which is an IBM initiative,

  • we have these courses people can take

  • and learn about data science,

  • but at the same time we provide this cloud based environment

  • for not only analytics,

  • but also for working with big and small data.

  • So one of the products that is integrated

  • with Big Data University is Data Scientist Workbench.

  • Data Scientist Workbench is an internet based solution,

  • you log in and the moment you log in,

  • you now have access to some

  • very advanced computing environment.

  • As simple as R and Rstudio and data

  • and algorithms to define the data set using OpenRefine,

  • but also the ability to work with very large data sets

  • using technologies like Spark.

  • So, the advantage of working with Data Scientist Workbench

  • is not only that you have the ability to work with

  • these advanced algorithms and two computing platforms,

  • but you also have the ability to work with

  • very large data sets because Spark

  • is integrated and it's all in the cloud,

  • you don't have to maintain it,

  • you don't have to download it,

  • you don't have to worry about updating it.

  • All is being done for you in the cloud

  • by the Data Scientist Workbench.

- Cloud is a, it's a godsend for data scientists.

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A2 初級

什麼是雲【數據科學101】? (What is the cloud [Data Science 101])

  • 82 12
    陳賢原 發佈於 2021 年 01 月 14 日
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