Chinese Internet

An article written April 12, 2012 in The Guardian, explains that there is a lot of speculations over the cut of all foreign websites for an hour long that evening. Apparently this was an hour of government officials testing how they can strengthen their censorship, leaving many Chinese citizens worried. While they were encouraged to believe it was just a failure in the internet, an executive at the Data Center for China released a blog urging people to think otherwise. Apparently this is all to branch out the "great firewall" that is overtaking China. The ministry of information technology said it was to investigate the situation but many are still concerned with the lack of information that average citizens have access to. Many people are worried that their government is in too much control of their everyday lives and what information they'll be able to access in the near future. With all the filters the "great firewall" of china has put on its citizens, bloggers are begging to think they might be soon disconnected from the world.

Another article I read that was posted only hours ago. This one discussed the recent attack that china has had on its own citizens, by arresting more than 6000 people. They didnt stop there, after deleting Sina Wiebo (China's modern day facebook) by deleting almost every opinionated comment, they went through and censored several more social media websites. This article focuses the attention on how this might backfire for china. With its  more than 500million  users and its online retail value to be set to be $364 billion by 2015, censoring their internet, could mean putting an end on their central market. It also brings up the point that the Foreign Direct Investors will start to dramatically decrease if China censors the information they have access to before investing with them. China's fears should include, the thousands of money spend on closing down the internet as well as how its disrupting the innovation of the internet.

The third article I read, discussed an event on April 3,2011 a very inspiration Chinese artist named Ai WeiWei was sent to jail for his attempting to create the arab styled revolution protests. The government released him but this action served to show the other citizens how much control China really has over its country. However, this isn't stopping WeiWei and his supporters who claim that the they are now "behind" in the generation due to the censorship on the internet in China. Current citizens dont even have access to popular sites including twitter and facebook. They believe free discussion could lead to corruption of the country. That is why the government either hides or deletes potential controversial information for its citizens, leaving them in a bubble.

The last article I read is quite interesting because it gives the opinions of Googles co-founder Sergey Brin. In this article it shows how Brin goes from having such confidence that the Chinese government couldnt censor the internet to fear as to how much control they have. The fear comes from the limitations that China has been able to restrict, meaning they are slowly changing the innovation of the internet.
His fear includes the support other countries might feel by China's actions. With Googles international market, there is a lot on the line by having too much censored.

Facebook Infographic

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This infographic laid out my social life on facebook pretty well! For people who aren't familiar with who I am at all, it hit the nail on the head as to who I interact with most frequently. The photograph it framed up top is my "profile picture." Then the site filters my facebook and shows the most popular status that I have posted. It shows these ratings based on how many people have "liked" that status in correlation to other statuses.

I thought it was really interesting that it showed me a ratios for how commonly people liked or commented on either my pictures or my statuses. It then filtered my facebook friends and showed how many were men and female and from those it showed how many were in a relationship. It rated my top 5 friends in correlation to how much they've interacted with me on facebook. It then showed how many times I've smiled in my pictured vs did unknown gestures.

Towards the end it showed my friends based on where they lived and showed me a world map of where most are located. Another cool feature was how it filtered how many people on often I have with me on my picture (3.4). The top picture of the monster describes my interactions on facbeook. The girl holding the #1 finger shows i've gotten more than 100 likes on my page. There were two pages that it was unable to retrieve which was my friends birthdays as well as the friends I communicate with the most. That is probably because my friends have their profiles on private, only allowing friends to see such information.

Twitter Sentiment

 
Twitter is based on the idea of expressing ones thoughts. The unique thing about twitter sentiment is its ability to combine these thoughts into what the majority is thinking. With these two designs it shows that most students (particularly at UGA all have the same things in mind. I would be interested to search products that I would want to use or possibly movies that I would want to see and get my peers' opinions. This is a very useful thing for companies to use as banners and exercise their consumers opinions in a cheaper more affective manner.

Tresata-Hadoop as a Service

 Tresata


Tresata works with the financial service industry to find big data solutions in their business problems.Tresata is using hadoop to power Big data and Analytic platform aiming to help the financial data industry. They have built the only (hadoop based) platform that stores, manages, and analyzes data used by financial based companies. Tresata's platform ties unique data products and large data algorithms to understand business problems.

A product Tresata offers is an online software that is available to instal through the internet. This software allows for storage, processing, retrieval, and analysis of large financial data. This is the first financial, hadoop powered, anaylitic application.

Tresata also carries services throughout the banking industry in small workshops that help educate clients on new tools, or technologies that helps them manage large data sources. Tresata also recently partnered with SI companies and assisted their clients with integrating the BIG Data platform in their technology system. This leads to solving business problems that companies would previously get stuck in.

 I believe that Tresata is one of the essential platforms needed in most businesses today. With the large amounts of data that business are presented, it can be frustrating relying on a product that works and is efficient for your needs. Tresata seems to go beyond a clients expectations and enhance the flow of large scale data and converting it into meaningful information. In the financial aspect, businesses needing to keep up with information is key and not many programs promise the service that they do. I really like that they have workshops where they teach people in the financial industry of the new technologies and tools. most of the time, people get caught up in work and don't look for such things. I think this could be a great time and money saver to businesses.

Cloudera

1. Why is Hadoop a "Big Deal"? Hadoop is a big data management system. Hadoop allows easy storing and process of large data. We see it in most sites visted today, including facebook, google, and yahoo. It makes it easy for users to build large scale systems. 2. Who are Cloudera? Cloudera consist of a community of developers including, Yahoo, facebook, lastfm, and quantcast. From these developers, cloudera builds a distribution from their codes and add features from customer requests and give it back to their community. 3. What is PIG? Pig was developed at Yahoo. Pig defines a new language called Pig Latin, designed for exploring large data set. Makes it easy fast rapid analysis of data. It's great for researchers who are familiar with programming. It allows you to write programs easily and act on them. 4. What is HIVE? Hive was developed at facebook Hive is similar to PIG. This is a data warehouse and query language. Allows you to collect data and impose structure on that data later, so you can define data after collecting it. This is great for statisticians who are already familiar with their data. It was used in facebook to empower people to look at the data they were collecting and make predictions from them. 5. What is Cassandra ? Cassandra helps create high scalable databases that is can then be distributed. It i being written in Java. It alo gets replicated in the data centers and makes sure that if the whole data center crashes no data is lost. It is present in facebook. A lot of graet data models have been created from it. 6. What is Mahout Mahout is the program that allows different sites to took user behavior and make different recommendations from items users might like. It also clusters information from documents and groups them in related documents. Mahout allows for classification which is the ability to take documents from different categories and assign them to similar labels. It allos to make things such as a list for other items of interest from an online shopping cart that one might have.

Energy Production - comparing the US and China

The first chart shows the difference in GDP per capita and energy production. The two countries we are comparing are China and the US. In 2010 (the latest data recorded) we only see the united states with 1.74 million kt of energy produced, that comes to be $37,527.35 per capita. That makes the United States the highest producer of energy of that year. We would think that it has the most GDP per capita since its creating the most energy, but this chart shows exactly the opposite. Some of the least productive energy producers have the greatest GDP per capita. A good example for this is Luxemborg, with 103.98 kt of energy produced and a shocking $52,422.46 GDP per capita. However, going on to compare the US and China in 2009 we see a slight change in our story line. Here, the United states was outbeat by China who produced 1.98 million kt of energy only had $2,032 GDP per capita. This was different than the US at the time who was behind with 1.70 million kt of energy produced with a greater GDP per capita $38,335.78. These numbers are interesting to analyze for what to expect from the future. We see this constant pattern going back to 2007. Why? Its interesting to note that a big difference between the 2 biggest energy producing companies and their GDP's is population. Therefore in order to have hopes for china to overcome their low GDP we might need to give it more time to see if a decrease in the population would have any affect on that. Also, the United states seems to We would expect China to have a greater per capita GDP however there are things that we must consider, like the difference in population! With the greater amounts of energy produced in 2009, the GDP per capita, started to decline. It will make an interesting study to watch and see if the gradual drop in GDP will have an affect on the energy production. In my second chart I compared CO2 emission (per capita) with the adjusted net national income. For this chart the latest recorded data was in 2008. The size of the circles represents the population in each country. The two that I will be comparing is China and the United States. The US has a population of more than 304 million, and China has a population of more than 1.3 trillion. The story line shows that ever since 1970 the US has had the highest net national income and exponentially increased every year. There is a difference in the CO2 emissions though. In 1970, it was recorded that they had 21.11 CO2 emission per capita this is a small difference from 2008 where the CO2 emissions were 17.94. Now comparing the net national income, we see in 1970 the US ranking in more than $924 billion while in 2008 they've had more than $12.2 trillion. This should be a concern for the citizens as well as environmentalist trying to protect people from potential harm caused through it. With nearly $10 trillion net income increase there should be more attempts to decrease the CO2 emissions. Now comparing similar the same data set to China, we see a little difference. China starts with more than 85 billion net national income in 1970 and increases to 3.7 trillion by 2008. Although this is a great increase in the national income, its still not as large as the united states' increase. However, with China, we see CO2 emissions per capita starting at .94 in 1970 and increasing to 5.31. In china an opposite pattern seems to occur with a gradual increase in CO2 emission as time passed. This might be to their country developing gradually. Either way, there is enough evidence in both the US and China to note that CO2 emissions need to be taken serious and dealt with in order to lessen the amounts their citizens are exposed to. The increase in both the countries net income shows a positive incentive to move towards investing in fighting greenhouse gases.

Many Eyes

My first chart tells a story through a bar graph. In this bar graph we see the number of divorces rates among employed workers vs unemployed workers. Here, the highest bar of divorced and married people is separated by gender and age. It is interesting to note the slight difference between the unemployed, who are more likely holding onto their marriages than the have employed who aren't. It is important to note that the data set was based on workers in the United States, so this doesn't show the overall pattern for marriages around the world. My second visualization shows a bubble chart. This bubble chart tells a story of illegal immigrants per country. Here the bubble sizes matter in relation to how many illegal immigrants reside in America. The biggest data set here shows that Mexican(4,808) citizens are the most illegal immigrants in America. The second biggest illegal immigrants come from El Savadore(189). It also shows the least number of illegal immigrants come from Canada (47). It is important to note these numbers are in thousands. This information would be important to Federal officials who are control of such matters. The third visualization shows a scatter plot. This is an interesting study that shows the annual expenditure per race. Most races showed most money spent in the housing spectra. The races were in categories of White, Asian, and African American. The least amount was spent on public transportation and basic grocery items such as eggs and meat products. This information is important for marketers and working Americans to plan their expenditures.