HADOOP: MAKING SENSE OUT OF BIG DATA

“BIG DATA” is a term for a collection of a large and complex volume of both structured and unstructured data. It is so big and complex that it is very difficult to process it using traditional software and techniques. Example of Big data would be Petabytes or Exabyte of data consisting of trillions of information about millions of people. Organization often faces a problem in creating, manipulating and managing a big data. But a successful interpretation of big data provides a competitive edge to the firm as it can provide a real time information.

Hadoop is an open source software that supports the processing of Big Data. It makes possible to run applications on systems with thousands of nodes involving thousands of terabytes. Hadoop makes sense out of your big data and reveals answers that have always been just out of reach. In order to gain a competitive edge by making a sense out of a big data, there is no brighter lure than Hadoop for an organization. But in order to take best use of Hadoop a firm has to understand Hadoop and then implement it in their data cloud.

•  Hadoop doesn’t works well with the structured data. Hadoop is ideal for the data from the sources like social media, documents, graphs etc. i.e., data which can easily fits in rows and columns
• Transactional data are also not ideal for Hadoop
• Hadoop works best when it is deployed in situation such as index buildings, pattern recognitions and sentiment analysis i.e., Hadoop should be integrated within existing IT infrastructure of firm, it should not replace the existing infrastructure
• Hadoop is linearly scalable, firm has to increase storage and processing power whenever there is an addition in number of nodes.

      

      Conclusion

       In order to have a competitive edge over competitor a firm has to analyze its Big Data more effectively than its competition and for doing so Hadoop is a best tool but in order to make best of use of Hadoop a firm has to understand that Hadoop should not replace the existing system but augment Hadoop with an existing system.

Refrences:

• http://www.cloudera.com/content/cloudera/en/why-cloudera/hadoop-and-big-data.html
• http://www.cio.com/article/708542/What_Hadoop_Can_and_Can_t_Do?page=3&taxonomyId=3028

NETVIZZ- A FACEBOOK’S ADVANTAGE OVER TWITTER

In my previous blog I blogged about Gephi, how simple and useful it is in analyzing social networks. You just need to import your social network data into Gephi. Here I would like to introduce Netvizz through which you can easily download your Facebook networks as a gdf file which you can then analyze in Gephi.

Netvizz Facebook application provides a tool that allows an easy way to export your personal Facebook data in a gdf format. Twitter doesn’t have an application like Netvizz and it is very difficult to extract twitter data in order to analyze it. Therefore Netvizz is an advantage of Facebook over twitter in providing easy access to their personal data in the form of gdf file which can be analyzed in order to find out some important implication. 

DATA ACCESS via NETVIZZ

It is very simple to use Netvizz. It is a part of Facebook directory and can be easily found out by typing Netvizz in Facebook search box. Netvizz requires user to log in with their Facebook account in order to use it.

Netvizz App Permission Request Page

First Netvizz will ask you to have an access to your Facebook friends’ connections. You have to grant this permission otherwise Netvizz will not work; users’ privacy settings are indeed relevant for interpreting the retrieved data. Remember Netvizz application doesn’t store any of the extracted data in a database and generated files are deleted in regular intervals. So it is safe to grant the permission to Netvizz.

Netvizz App Page

Next step is to open the application page and choose the network which you want to analyze in Gephi. If you have a very large number of friends it will take some time and at the end it will give you the option to download the gdf file of your Facebook data. This file then you can open in Gephi and analyze for important implication.

Students who want to use Gephi in order to analyze their social network data and find out some implication will definitely like the Netvizz and its simple use in extracting the data from Facebook whereas they will find it very difficult to extract data from their twitter account because of absence of a simple to use app like Netvizz in Twitter. Netvizz is definitely a Facebook’s’ advantage over Twitter for data analyzers.

Refrences:

• http://rieder.polsys.net/files/rieder_websci.pdf
• http://noduslabs.com/radar/netvizz-export-facebook-network-graph/

GEPHI and its implication in MARKETING

As a part of my course Web and Social Media Analytics under Dr. Sudha Ram (http://vishnu.eller.arizona.edu/ram/), I came to know about a free tool Gephi which is very helpful in analyzing a social network data through which we can find out various implications.

Gephi is a powerful social network modeling tool which is available free and you can download it from http://gephi.org/ . One of the most important advantage of this tool as a network analyzer is its simplicity to use. It does not require any special skills to operate. You just need to import your social network data into it and apply some easy algorithm to it. You will get a connected network with various clustering which can be visualized and analyzed in order to get some important business implications.

This picture shows a network of a Facebook data given to us by Dr. Sudha Ram in Gephi. This data is divided into four clusters according to some relationship which we can find out after analyzing each cluster individually. It is a very simple network with only 62 nodes and 1174 edges. But Gephi can very well analyze a network with 50,000 nodes and about 1 million edges.

In today’s world social media is a very powerful place of promoting one’s brand or product. Almost every brand is present in a social media mainly in Facebook and Twitter. Because these social sites have a very large number of subscribed users there is a need to analyze a brand performance present on social media. Through Gephi one can analyze its connections in social media and can easily find out a business implication like whom to target, how to position etc. based on the clusters formed out of Gephi. 

One of the most important marketing implications of Gephi network visualization is Targeting. You can easily find out the demographic of peoples or clusters and then can decide about targeting and positioning of their brand.

As a Marketing student I am very much impressed with Gephi and its simplicity to use. It is very much recommended for a student majoring in marketing and analytics to get familiar with GEPHI.