Outsourcing Data Science: What You Need To Know - InformationWeek

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Data Management // Big Data Analytics
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2/22/2016
08:06 AM
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Outsourcing Data Science: What You Need To Know

More companies are creating data science capabilities to enable competitive advantages. Because data science talent is rare and the demand for such talent is high, organizations often work with outsourced partners to fill important skill gaps. Here are a few reasons to consider outsourcing. What can go right and wrong along the way?

(Image: bkyst via Pixabay)

(Image: bkyst via Pixabay)

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DextroAnalytics
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DextroAnalytics,
User Rank: Apprentice
5/20/2016 | 6:37:33 PM
Re: Your article
Lisa,

Overall great article. You have captured different dimensions of outsourcing. The analytics industry is rapidly changing - massive wave of DIY tools, open source platforms, and internal data scientists. However, there is a fine line between being data-driven and having illussion of having everything in control because of data science.

1. Big companies who have army of data scientists are still struggling even when data science claims to predict who, why, what, when etc.

2. Tools and internal data science sometimes creates tunnel view on solving the problem. Most have access to same or similar data and mostly use similar statistical algorithms. It is only those who can find hidden nuggets that traditionalists can't - thats where the partnership with vendor helps.

3. Vendors have to be humble enough to transfer the knowledge and constantly innovate for survival. 

Just my two cents. 
LisaMorgan
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LisaMorgan,
User Rank: Moderator
2/28/2016 | 4:26:22 PM
Re: Great
You are absolutely right!
shamika
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shamika,
User Rank: Ninja
2/28/2016 | 5:07:08 AM
Great
Well I think this is a good initiative. However, it's important to look in to the confidentiality when working with third party partners.
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