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My first hands-on experience with Big Data

Big Data- Is it just another buzzword in the corporate world or truly the next big thing in the industry worldwide? The question did bug me for a long time that led me to browse through the internet reading various newsletters, journals and business articles on the topic. So, when we were supposed to chose a topic for our final year  project in MBA course, namely the Applied Management Research Project my immediate choice was this. However, implementing big data analytics without the knowledge of advanced statistical methods like support vector machine and  tools like Hadoop was a big challenge. So after studying various research papers I decided to go for text analytics, a  subset of big data and selected my favorite platform R for the same. The topic of the project is: Text analytics- An application on Indian stock markets. Objective was to check if top news of the day has any significant effect on the returns of Indian Stock market. The most widely followed composite index Nifty is…
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Cloud Computing Revisited

Cloud computing is an emerging technology, that has redefined the word "efficiency" in many ways. It is a revolution in the world of Information technology. Gone are the days when u had to download 100 versions of the same file each time it is updated by a team member and make a mess of your desktop. It’s the age to share and make optimal use of limited resources. As our professor Dr. Prithwis Mukerji always says “ when resources are limited, creativity is unlimited”
This edutainment video was made as a part of the IT business Application Lab assignment. Myself and my teammate Raviteja Lokireddy had a great time shooting this video and exploring the world of cloud computing. Special thanks to our friends Arun Kumar Kota, Satish Nemalipuri, Venkatesh and Shehzad from VGSoM, batch of 2014for their guest appearence.

Business Application Lab

Assignment 1: Create 3 vectors, x, y, z and choose any random values for them, ensuring they are of equal length,T<- b="" cbind="" nbsp="" x="" y="" z="">
Create 3 dimensional plot of the same 
> sample<-rnorm p="">> sample
 [1] 23.10381 25.85777 22.04959 43.53180 12.11174 37.23922 38.92648 22.77181 17.80844 30.41365 32.32586 37.09651 24.55097 19.85470 31.01534 29.70007 31.72610 22.26199
[19] 19.85826 36.94503 23.50247 18.00116 24.50004 27.57822 20.34054 17.32243 30.26892 19.03535 16.14514 28.81016 29.45099 23.10639 25.49178 35.95906 19.35419 23.04064
[37] 25.20819 18.83031 30.75433 19.14759 28.11077 25.91251 28.03618 33.34057 30.19792 25.07813 25.08856 26.12123 24.15002 22.09888
> x<-sample p="" sample="">> y<-sample p="" sample="">> z<-sample p="" sample="">> x
 [1] 22.77181 31.01534 27.57822 22.09888 24.1500…

Data Visualisation Tools

A picture is worth a thousand words- from simple daily affairs like finding a route, to the most evolved managerial concepts like BCG matrix or strategy issues like prisoner's dilemma, a picture or a diagram can help comprehend data in an easier way. In fact it often gives meaning to a raw un-organised data. Data visualization is the study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information".
An online data visualisation tool that I analysed recently is iCharts. It is an extremely simple yet useful tool by which we can plot graphs of multi-dimensional data, analyse the trends, share the results and also embed them in our websites and blogs. We can use this tool to analyse surveys and do market research. To avail most of the advanced features like connecting to an application, using analysis tools you need to be a paid user. The monthly  amount to be paid…

Business Application Lab

Panel Data analysis for "produc" dataset

models to be tested:
1. pooled
2.fixed
3. random

Tests to be performed:

pFtest : for determining between fixed and pooled
plmtest : for determining between pooled and random
phtest: for determining between random and fixed

1. load data
\
2. Pooled pool <-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" pooling="" state="" unemp="" util="" water="" year=""> summary(pool)



3. Fixed  fixed<-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" state="" unemp="" util="" water="" within="" year=""> summary(fixed)


4. Random

random <-plm data="Produc,model=(" e…

Business Application Lab

Panel Data analysis for "produc" dataset

models to be tested:
1. pooled
2.fixed
3. random

Tests to be performed:

pFtest : for determining between fixed and pooled
plmtest : for determining between pooled and random
phtest: for determining between random and fixed

1. load data
\
2. Pooled pool <-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" pooling="" state="" unemp="" util="" water="" year=""> summary(pool)



3. Fixed  fixed<-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" state="" unemp="" util="" water="" within="" year=""> summary(fixed)


4. Random

random <-plm data="Produc,model=(" e…

Business Application Lab

Panel Data analysis for "produc" dataset

models to be tested:
1. pooled
2.fixed
3. random

Tests to be performed:

pFtest : for determining between fixed and pooled
plmtest : for determining between pooled and random
phtest: for determining between random and fixed

1. load data
\
2. Pooled pool <-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" pooling="" state="" unemp="" util="" water="" year=""> summary(pool)



3. Fixed  fixed<-plm data="Produc,model=(" emp="" gsp="" hwy="" index="c(" log="" p="" pc="" pcap="" state="" unemp="" util="" water="" within="" year=""> summary(fixed)


4. Random

random <-plm data="Produc,model=(" e…