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11/26/2013
02:46 PM
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How Educators Can Narrow Big Data Skills Gap

With data scientists in short supply, the US must step up its game to compete globally, says educator.

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Susan Fourtané
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Susan Fourtané,
User Rank: Ninja
12/2/2013 | 1:44:24 AM
Re: Big Data Skills
Shakeeb,

"I have seen only limited number of people select their profession in the field of analytics."

You also have to take into account that it was not until recently that there was such an explosion in the big data field. Now the data scientists needed to cover such needs are more than a few years ago. 

As the demand grows, education needs to focus more on this field, and at due time more people will choose professions in the field of analytics. 

-Susan
Susan Fourtané
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Susan Fourtané,
User Rank: Ninja
11/30/2013 | 6:16:07 PM
Re: Educating the K-12 students first
shakeeb, 

There is a need for more data scientists. And the need will just increase as the world is generating more and more data as we speak.

You won't get more data scientists unless the kids who are today in their elemenatry school years find a real interest in mathematics, and statistical analysis.

Schools need better mathematics teachers who are passionate enough to teach mathematics in a real engaging, interesting, and fun way. Otherwise, forget you will get enough data scientists in the future.

This is why the ficus should be on elementary school kids. 

-Susan
shakeeb
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shakeeb,
User Rank: Black Belt
11/30/2013 | 1:01:10 PM
Re: Big Data Skills
I agree with you shamika. The gap in big data skills has to be reduced by giving the required know how on that area. At the same time I have seen only limited number of people select their profession in the field of analytics. 
shakeeb
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shakeeb,
User Rank: Black Belt
11/30/2013 | 1:00:37 PM
Re: Educating the K-12 students first
@susan. Yes you are correct. The knowledge has to be given from the primary level for them to select the path during the higher studies.
Susan Fourtané
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Susan Fourtané,
User Rank: Ninja
11/30/2013 | 12:42:34 AM
Re: Educating the K-12 students first
Shamika, 

If you want to improve the knowledge you need to start from the essentials, i.e. teaching mathematics in a better way to elementary school students.

You also have to make mathematics and statistics interesting enough to the young kids so they choose a career which will lead them to become good data scientists later.  

You say: " the best method is to provide the necessary knowledge about big data and the importance of having these concepts build in our organizations." 

When and where do you that? 

-Susan
shamika
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shamika,
User Rank: Ninja
11/29/2013 | 11:44:19 PM
Re: Big Data Skills
@aditshar you are very true. The most important skills would be the knowledge in mathematical and statistical analysis. 
shamika
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shamika,
User Rank: Ninja
11/29/2013 | 11:42:15 PM
Re: Educating the K-12 students first
I think the best method is to provide the necessary knowledge about big data and the importance of having these concepts build in our organizations.
Susan Fourtané
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Susan Fourtané,
User Rank: Ninja
11/29/2013 | 4:25:48 AM
Educating the K-12 students first
Educating students who might become data scientists in the future is important. But, as the article says, education should start with K-12 students.

Educated citizens will be able to use the knowledge in any other situation, as it was also started.

Maybe looking at successful education programs from other other countries could help. 

-Susan
Susan Fourtané
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Susan Fourtané,
User Rank: Ninja
11/29/2013 | 3:46:26 AM
Re: Big Data Skills
Li Tan, 

"I do not mean to say that you cannot become a data scientist without them but it may become rather tough." 

Data science is based on mathematics, statistics, and data mining. I believe it's impossible to become a data scientist without those skills. 

-Susan
Li Tan
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Li Tan,
User Rank: Ninja
11/27/2013 | 10:37:12 PM
Re: Big Data Skills
The traditional programming skill is needed but that's far from enough. You don't need to be mathematicians but the background in statistics, data mining is necessary. I do not mean to say that you cannot become a data scientist without them but it may become rather tough. 
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