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Data Science Projects - Success Rate

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Anthamidhya
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Posted on Friday, January 18, 2019 - 09:35 pm:       


Redbull:



Redbull:



Fraud alerts, recognizing money laundering acts, services side credit modeling ilaa, optimal resource allocation, customer service lo regulatory compliance etc etc saala cheyyochu
 

Saidabad
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Posted on Friday, January 18, 2019 - 05:33 pm:       


Gochi:



vachina answer manaki nacchakapothe we cannot say its not success...probably there is no pattern in the data at all...intha money spend chesaam kaabatti show me some results ante mana desi companies ni pettukondi, meeku kaavalsina result choopisthaai (result ni mundey coding chesi expected result oche laaga)...Data Science/ Machine Learning is all about identifying a pattern or behavior...we cannot forcefully bring out a behavior..nor we can go with a presumed conclusion and ask data analysis to support it...




2 things...
1) preassumed concepts ni prove cheyataniki intha srama avasaram ledu, maname edo cookup cheyonchu, thats not even a consideration

2)business acumen chala stron vundali besides business chala ardham kavali

nenu chebutondi ade bhayya...very few practical use cases vunnayyi ani, prati daniki vadalemu, vadina earth shattering thought provoking results ravu




Redbull:

pot on..doubt emi ledhu..already most of banking world lo ee data science ani last 2-3 years sevulu moosi saava gotti ipudu madatha peduthunnaru..

end users..emi saadistundhi vayya nee solution ani pedhavi virustunnaru




hmm so this is happening, I was looking for such insight
 

Gochi
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Posted on Friday, January 18, 2019 - 04:35 pm:       


Saidabad:

Requirements are clear, data is there but solution apply chesthe results lo not much improvement. Ante memu Maa tools lo calculate chesina reorder point ki data science vallu proper chesina daniki not much dufference. So we are not seeing the value add, data Science looks good theoretically but not so succeduti when applied to real business problems ani doubt.




vachina answer manaki nacchakapothe we cannot say its not success...probably there is no pattern in the data at all...intha money spend chesaam kaabatti show me some results ante mana desi companies ni pettukondi, meeku kaavalsina result choopisthaai (result ni mundey coding chesi expected result oche laaga)...Data Science/ Machine Learning is all about identifying a pattern or behavior...we cannot forcefully bring out a behavior..nor we can go with a presumed conclusion and ask data analysis to support it...
 

Redbull
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Posted on Friday, January 18, 2019 - 04:13 pm:       


Saidabad:

data Science looks good theoretically but not so succeduti when applied to real business problems ani doubt.




spot on..doubt emi ledhu..already most of banking world lo ee data science ani last 2-3 years sevulu moosi saava gotti ipudu madatha peduthunnaru..

end users..emi saadistundhi vayya nee solution ani pedhavi virustunnaru
 

Redbull
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Posted on Friday, January 18, 2019 - 04:11 pm:       

so called data science and moderen AI etc..have just 10-15% use cases.

ee banking lo data science is pedha boothu..what the heck u want to do with customer transaction data. from customer point of view all i need is good saving rate on my savings and less interest on my borrowings..

amazon, social media feed is different use case..same banking vaallu guddigaa foloow ayipodham ani choostunnaru..
 

Janasena
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Posted on Friday, January 18, 2019 - 03:16 pm:       

3-4 months is very low..
Normally the training / exploration/ takes 4-6 months based on the dataset and complexity.
 

Janasena
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Posted on Friday, January 18, 2019 - 03:15 pm:       


Vjawarrior:

how to start learning data science...do we need to be a good p[rogrammer to become a data scietsit...asalu ela start cheyyali...future is all data science antunnaru...
blockchanin padukunnatlu undi...no one talking abt it




Azure/Google/AWS has ML learning platforms..
edx lo courses vunnayi pure data science meeda..chosuko
Side na R/Python/SaS nerchukoo

You need to know which algo to apply based on use case..
 

Vjawarrior
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Posted on Friday, January 18, 2019 - 03:12 pm:       


Janasena:


how to start learning data science...do we need to be a good p[rogrammer to become a data scietsit...asalu ela start cheyyali...future is all data science antunnaru...
blockchanin padukunnatlu undi...no one talking abt it
JP Rocks: atu gaa paaare murikkaalava - aa rojule veru kada annai

OT's legendary vijayendra varma review lo aa kondalu konalu loyalu sarasa sallaaaaapaalu type lo aa cycle, danikunna springu seat, kaaanthini vedajalle light, sahanaaaniki maaru peru la ooosalu, moortheebhavinchina manavatvam laati methati tires


thaathaa, enti maaakeee raatha
 

Janasena
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Posted on Friday, January 18, 2019 - 03:00 pm:       

Data Accuracy, Filtering bad data kosam kooda ML models vaduthunnam
 

Janasena
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Posted on Friday, January 18, 2019 - 02:59 pm:       

Data Science fail avvatam vundadu...Data scientist fail avvochu

We are working with Data scientists whose models predict with 95% Accuracy, which is very critical for the current customer business running with out any hiccups
Finance sector lo Fraud alerts, and many other things kooda predict chesthunnayi successful gaa...
 

Saidabad
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Posted on Friday, January 18, 2019 - 02:18 pm:       


Scout75:

can hit our targets like 4/10 atleast in my project a




Can you give examples of usecases that were successful and not as well, thanks
 

Scout75
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Posted on Friday, January 18, 2019 - 02:06 pm:       


Saidabad:


from my point of view I would try to apply to atleast a few accounts and check if your data points match before and after a DS . If it didn’t may be you can analyze your missing business case . I’m might be wrong though since I don’t know the problem or the solution provided
 

Saidabad
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Posted on Friday, January 18, 2019 - 02:03 pm:       


Maverick:




Exactly imagine my feelings when they were presenting their solution, 6000 products lo Nenu 200 skus isthe 2 solutions anta
 

Saidabad
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Posted on Friday, January 18, 2019 - 02:00 pm:       


Vjawarrior:




Datascience meeda I am very skeptical 🤨, yet to see any real value

This thread is to learn about successes and real business results people might have seen in their projects
 

Vjawarrior
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Posted on Friday, January 18, 2019 - 01:59 pm:       


Maverick:


mav...data science nerchukunnavaa? hyd lo IIT candis have an excellent institute for datascieence...many people learnt there and got some jobs here...later they are moving to amazon
JP Rocks: atu gaa paaare murikkaalava - aa rojule veru kada annai

OT's legendary vijayendra varma review lo aa kondalu konalu loyalu sarasa sallaaaaapaalu type lo aa cycle, danikunna springu seat, kaaanthini vedajalle light, sahanaaaniki maaru peru la ooosalu, moortheebhavinchina manavatvam laati methati tires


thaathaa, enti maaakeee raatha
 

Saidabad
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Posted on Friday, January 18, 2019 - 01:58 pm:       


Biggboss:




One of the usecase - we want to figure out reorder points for our products

Requirements are clear, data is there but solution apply chesthe results lo not much improvement. Ante memu Maa tools lo calculate chesina reorder point ki data science vallu proper chesina daniki not much dufference. So we are not seeing the value add, data Science looks good theoretically but not so succeduti when applied to real business problems ani doubt.
 

Maverick
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Posted on Friday, January 18, 2019 - 01:56 pm:       


Saidabad:

200 skus were broadly categorized into 2 groups and solution provided.



There's a cacophony in the truth, A melody in lies and it accompanies one on every journey, From the lows to the highs
 

Vjawarrior
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Posted on Friday, January 18, 2019 - 01:52 pm:       

saidabad....amazon is hiring data scientists ..160k with 50k sign on...2-3 years exp in Data science is enuf
JP Rocks: atu gaa paaare murikkaalava - aa rojule veru kada annai

OT's legendary vijayendra varma review lo aa kondalu konalu loyalu sarasa sallaaaaapaalu type lo aa cycle, danikunna springu seat, kaaanthini vedajalle light, sahanaaaniki maaru peru la ooosalu, moortheebhavinchina manavatvam laati methati tires


thaathaa, enti maaakeee raatha
 

Saidabad
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Posted on Friday, January 18, 2019 - 01:52 pm:       


Scout75:

Did you implement any solution provided or do you think that�s like a far away target to your organization. What did you predict would be coming out for your assignments given to data scientists.




Yes!! Let’s say solution was to identify reorder point for high revenue products, either the solution is too broad and did not consider the variability associated with each product so can’t be really applied . As you said 4/10 success rate kooda choodaledu.

First hire chesindi mgmt consultant ne
 

Biggboss
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Posted on Friday, January 18, 2019 - 01:50 pm:       


Saidabad:

Not worried about the technology they are using, I am referring to the success of the proposed solution




I was not trying to highlight the technology part, I am trying to say with good Data Scientist and with clear requirements and data - it's not a hard problem to solve
 

Biggboss
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Posted on Friday, January 18, 2019 - 01:48 pm:       


Saidabad:

Ofcourse, millions of past selling and buying patterns, product offerings, diff GTMs and RTMs, promotions and other discounts - ivi anni analyze chesi we want to figure out reorder points for our products




What exactly is your use case?
 

Saidabad
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Posted on Friday, January 18, 2019 - 01:48 pm:       


Biggboss:




Not worried about the technology they are using, I am referring to the success of the proposed solution
 

Saidabad
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Posted on Friday, January 18, 2019 - 01:46 pm:       


Vishvak:




Ofcourse, millions of past selling and buying patterns, product offerings, diff GTMs and RTMs, promotions and other discounts - ivi anni analyze chesi we want to figure out reorder points for our products
 

Scout75
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Posted on Friday, January 18, 2019 - 01:42 pm:       

How do you define success . Did you implement any solution provided or do you think that’s like a far away target to your organization. What did you predict would be coming out for your assignments given to data scientists.

For example I work for a big bank . Our Business has specific targets and they ask us to provide data for that business cases . We do deliver a lot of them kani more than 50% invalidate avuthayi as in every data point they find some abnormality but we can hit our targets like 4/10 atleast in my project and they are happy about it . Again like I said it depends on how you see your business case with the solution provided and how you want to apply it . When you think the solution provided to you is not applicable at your present organization level why not hire a management consultant who can think a bit outside the box or give your data scientist a specific case and ask him the things that you want to see
 

Biggboss
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Posted on Friday, January 18, 2019 - 01:38 pm:       


Saidabad:

200 skus were broadly categorized into 2 groups and solution provided.




Are you doing SKU categorization?

I am currently working on Product Categorization - our DS engineer was able to build a quick solution in a week using Tensor Flow, AWS Rekognition and get decent results :-)
 

Vishvak
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Posted on Friday, January 18, 2019 - 01:37 pm:       


Saidabad:


Is that really a data science problem?

Vi veri universum vivus vici
 

Saidabad
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Posted on Friday, January 18, 2019 - 01:33 pm:       

Folks

Looking for feedback on successes you have seen on data science projects

Initially we outsourced the effort, it took them good 4 months to understand our business case, nuances of various driving factors. When they delivered, I felt solution proposed was several feet high. 200 skus were broadly categorized into 2 groups and solution provided.

Next we hired an in-house data scientist, same story is getting repeated. He was hired to apply the above solution to prove the concept as well as work on other projects. I have turned into a data science skeptic now.

Looking for real time successes.

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