Big Data Supplants Social Media Marketing in India

Prof. K Adisesha Prof. Praveen Moses HOD Computer Science Department HOD Computer Science Department Bangalore City College Aditya College

Kalayannagar, Bengaluru Yelahanka, Bengaluru

adisesha1@rediffmail.com prvn.moses@gmail.com

Mob:9449081542 Mob:9738065017

Big Data Supplants Social Media Marketing in India

Abstract

With the biggest steps imparted by the Government of India on digitization and cashless payment systems introduced in India. Big Data almost negates social media marketing as distinct from the rest of your marketing efforts. It allows you to compare apples to apples instead of apples to oranges, as it were. It acknowledges that, in a manner of thinking, all content nowadays in India is social content.

The best marketing approach for any business today, therefore, is to make allies with Big Data— which is to say: learn to understand and make productive use of it. As the McKinsey & Company report showed, the power of information can help you increase your productivity, improve your decision-making, and lower your costs. Perhaps most importantly, however, getting savvy with your own data helps you to stay competitive with those in your industry who are already using it to optimize their own efforts. Because the biggest impact of, big data on social media marketing strategies may just be the threat it poses to anyone who ignores it.Social media analytics tools are like life-sustaining organs for marketing professionals, as they are the simple ways for them

to identify what’s happening around them in the digital world, especially in social media

channels. Before they spend even a single penny from the wallet, it is imperative to know what

the customers are saying about them and what works and what doesn’t… Understanding the

customers is key in order to get great results. Social media analytics tools all do the same, of course in their own ways

Key words: Big Data, Digitization, Decision-making, Social media marketing, Social media analytics tools

1. Introduction

Nowadays, humans and machines connected to the Internet produce a huge amount of data that need to be collected, analysed and meaningfully used. In an international survey conducted on emerging trends in multi-platform shopping on the latest tech trends and consumer habits that are transforming how, where, and why we buy it revealed that nearly about 80.3% Indians don’t want to share their personal details while shopping online. On the other hand they create

voluminous data using different social media technologies. Machines (e.g. sensors and devices) create data that is transmitted to computers via the Internet. Various new technologies emerged to cope with ever increasing amount of data of different types and originating from disparate sources. For example, Big Data technologies contribute to solving problems related to volume, variety, variability, velocity, and veracity of data. Big Data analytics tries to find hidden patterns in data for decision making purposes. However, there is need for technologies that could solve semantic interoperability problems of data produced by humans and machines. In general, these problems could be solved by semantic technologies like Linked Data technologies and ontologies.

In the nearest future, semantic technologies will significantly improve machine understanding and interoperability of data. In this paper, we review and evaluate developments of emerging Information Technologies for capturing data from humans and machines like social media and Internet of Things (IoT). We also discuss Big Data technologies for management and analysis of these data and Linked Data technologies for semantic interoperability and linking data and Technologies.

Results of large number of studies on research and technology trends show that due to ultrafast Internet connection there is emerging a future web that will be a web of linked data and devices enabling real-time aggregation and analysis of extra large amounts of data.

 New Predictive Strategies

Fortunately, this inseparability of social media and Big Data empowers new marketing strategies. For one, the sheer breadth and scope of Big Data allows for the creation of more predictive approaches to analysis. This means marketers can now see with increasing clarity into the future to gauge the likely effectiveness of a strategy, rather than relying exclusively on past performance. This will foster the development of new approaches geared at predicting customer behavior, and can help limit the amount of costly and timely A/B testing a marketer would have to perform. A report by McKinsey & Company, for example, revealed that by using Big Data a retail business can potentially increase operating margins by over 60 percent.

 Customized Algorithms

Most excitingly, perhaps, this shift toward Big Data will also usher in an era of customized algorithms, allowing individual companies to analyze their marketing efforts in hyper-refined terms entirely distinct, and in all likelihood not even relevant, to their competitors. The benefits of this to any business are twofold:

1. You no longer have to pay such fierce attention to what your competition is doing and can focus more internally on making best use of the data you have at hand;

2. You and your competitors are not all playing by the exact same playbook, vying for the exact same stats across the exact same platforms.

The proliferation of this new customized form of data analytics will empower small businesses with limited resources to compete on a more even playing field with even their bigger, wealthier competitors. More and more marketing success will be measured not by the quantity of interactions with your data but the targeted relevance of it in relation to your own specific goals and objectives.

The best marketing approach for any business today, therefore, is to make allies with Big Data— which is to say: learn to understand and make productive use of it. As the McKinsey & Company report showed, the power of information can help you increase your productivity, improve your decision-making, and lower your costs. Because the biggest impact of big data on social media marketing strategies may just be the threat it poses to anyone who ignores it.

In India Technologies such as cloud, mobile, big data, analytics and social media have restructured the way the world functions and organisations are embracing these technologies based on changing business requirements, Professionals want to upskill to stay relevant and increase their chances of landing better jobs, according to Simplilearn’s 2017 Career Wishes survey of 8,700 executives carried out on social media.

Professionals actively think about their careers at the beginning of the year and resolve to acquire new skills to land the jobs of their choice. The survey – carried out on Facebook and Twitter – reflects the changing aspirations of professionals regarding new technologies

What is big data?

“Big data is an all-encompassing term for any collection of data sets so large and complex that

it becomes difficult to process them using traditional data processing applications.”

Big data refers to massive volume of structured and unstructured data which is expanding on three sides as shown in the image below.

Fig: 3 Vs of big data

The currently used definition of big data was proposed by Doug Laney in 2001. He proposed the 3 Vs of big data: Volume, variety, and velocity, and estimated that worldwide information is growing on at 59 percent annually, on the least.

How big is big data?

Are you aware of terms like petabyte (PB) and exabyte (EB)? Do you know how big is that? One exabyte is 1024 petabyte, and one petabyte is 1024 terabyte, and 1 terabyte is 1024 gigabyte. This is how big a exabyte or a petabyte is. And big data is as big, if not bigger (which hardly is the case), it is. As per IBM, we create 2.5 quintillion bytes of data every single day, which means that almost 90% of data available in the world has been created in the last 2 years. This is huge.

All the pictures that you share, all the smiley that you post, all the videos that you shares, all your likes, comments, and shares, tweets, blogs, videos, posts, links, data from GPS signals, etc., adds up to 2.5 quintillion bytes of data every day.

Is it a good or a bad news?

Like everything else, it depends on how you take it. Big data can be a boon for business (and also for social media campaign) if harnessed effectively, but if it is not used to its capacity, collecting it, storing it, and maintaining it can be a very, very expensive affair. To help you understand its business use, an example of the way eBay uses big data should be sufficient. eBay uses big data for search, merchandising, and customer recommendation using 90PB data on consumer transactions and behavior on its websites across the globe. The shopping giant stores the data on 3 systems: in 7.5PB and 40PB warehouses, and 40PB in commodity Hadoop. The company is using big data to build a customer-friendly shopping ecosystem to assist its customers buy the things they want.

How does it affect social media?

As pointed above, big data is a massive collection of data from various sources (variety) coming at various speed (velocity), and in various quantity (volume), and social media websites are collectively responsible for adding massive chunk of data of all three kinds to the big data pool. But unlike other data sources, information produced and collected by social media websites are unstructured, and it is so enormous in volume that it is not humanly possible to collect, process, and manage such a huge set of unstructured data. It even falls out of range of commonly used software applications. But the scenario is not all that bleak. There are tools to help you make

sense of onslaught of messages sent to and fro on various social media platforms by bringing all together and providing a structure to it, and making it useful for marketers.

If you want to get a glimpse of how confusing it can be, go through a twitter feed of any popular brand, and also to its Facebook page among other social profiles (variety in big data) should you wish to be more confused, and then try to make sense of this all from a marketing point of view. And here we are just talking about making sense of an instance of spontaneously generated, untagged, and uncategorized data churned out. What will it be like if we factor in all the data which was generated before now, which will generate hence forth! Add to this the data being generated now, as you read this, in real time (the velocity aspect of big data).

Some facts about big data and social media

1. Facebook takes in 500 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)

2. Twitter produce 12 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)

3. Facebook tracks every computer IP a user has logged in from, and other users who have logged before and after you from the same computer up to 800 pages size of data per users. (Source: com)

4. More than 4 Billion hours of videos are watched on YouTube each month. (Source: IBM Big Data Hub)

5. More than 30 billion pieces of content is shared on Facebook each day. (Source: IBM Big Data Hub)

6. By 2016, there will be 18.9 billion network connections, i.e., 2.5 connections per person. (Source: IBM Big Data Hub)

How big data helps in social media marketing

In the wake of changes brought in by big data, a brand needs to stop hiring a college student and fresher to curate its twitter feed or Facebook timeline, or any of its social profiles, for that matter. The brand also needs to stop guesstimating the future course its prospects and consumers will take and waste money based on that. Instead a brand should look for more and more data on its customers and prospects, other than what they share with you through their various interactions. In this, big data can help you a great deal. It can help you find out:

 Who buys from you?

This is as relevant as relevancy goes. In order to build a relationship and foster loyalty, the first and foremost thing you need to know is who is your customer, and that too not only in the demographic sense as suggested by market segmentation strategy of yore. Market segmentation

is not sufficient anymore. Now you need to know more about your buyers’ preferences, places

they hang out at, the things they talk about, the issues they are concerned with, the topics that excites them, etc., to target messages better on social media.

 How your customers feel?

It is not just the customers’ life that you should be interested in. In order to make your messages more useful for your brand and your customers you also need to gauge customers’ sentiment

around your brand and your competitors. Big data can help you understand your customers’ sentiment about your brand as well as your competitors.

 What they want?

This is one thing every brand tries to get a definite answer of. And I am not saying harnessing big data can give you a definite answer, but it will give you a much clearer picture of your

customers’ needs and wants than you can get from any other source. By tapping into their

interactions, things they talk about, things they say, products they buy, and places they visit, etc.,

big data can be help you estimate your customers’ demand.

 How do they satiate their information need?

By harnessing big data you can know a great deal about how your customers get the information they need. An understanding of the information sources your customers use to seek information you need, you can wisely select the vehicle to send your marketing message, and fine tune your message to match the vehicle and mood of your customers.

 How do they arrive at the buying decision?

The most important information a marketer wants is the knowledge of the process its customers took right from the 1st stage in the buying cycle; from gathering information to shortlisting product options to evaluating alternatives to shortlisting items to buy from to finally making the decision, and then its post-purchase interaction with the brand. This is a gold mine of information, and an access to it will help a marketer fine tune its social media marketing

campaign at each stage of customers’ buying cycle.

3. Scope of Study

Interlinking Information Technologies via Linked Data Information Technology connections

Linked data technologies are used as information infrastructure for integration of data from disparate sources. Comparing to mainstream technologies of relational databases, linked data technologies have advantages in cases where relational databases demonstrate slow performance and inefficacy, namely integrating (joining) data about a certain object. Another advantage of linked data technology is its ability to automatically integrate data from RDF database with data

from external sources like web data or sensor data, etc. Linked data could provide structure (RDF triples) and metadata to unstructured data like textual data or several data streams. At the same time, most RDF databases have currently slower performance (except join operation) than most commercial relational database systems. However, there are good commercial RDF datastores available (AllegroGraph, Big OWLIM, Marklogic, etc.) and also open source RDF database systems like Virtuoso, 4store, Bigdata etc. Comparing to web services technology that also enables to create data-integration services, linked data technologies are lighter, more flexible, faster and as such cheaper. Linked data technology is built on existing web standards (and open source RDF stores) that enables small and medium size companies to use it for development of data integration solutions. They might not have resources for building data integration solutions based on web services technology.

Fig: Interlinking Information Technologies via Linked Data

In the following Fig , most important connections of linked data technology with other information technologies considered in this paper are depicted. In addition, the figure also shows relationships between these other technologies.

 Big Data explosion is driven mainly by the following technologies:

 IoT that provides various sensors and connected devices collecting data about environment or human activities

 Social web generating a huge amount of data (e.g. audio, video, click-streams, etc.) by different online activities. In addition, social web networks share a huge amount of data of different types.

Linked data technologies play a central role of integrator of other technologies. Link data technology provides tools for the following types of data processing:

 Data fusion

 Structuring of semi- or unstructured data

 Providing of semantic metadata

 Linking of data

 Usage of common web standards for representation of data (e.g. RDF) and metadata or vocabularies (e.g. OWL).

Other technologies like Big Data, social media and IoT can benefit from applying linked data technology tools for processing collected data and developing new innovative applications. In the following subsections, linked data connections with each of analysed technologies are examined in more detail.

4. Conclusion

Today Big Data presents us with as many challenges as it does benefits. Whilst Big Data analytics can offer incredible opportunities to reduce inefficiency, improve decision-making, and increase transparency, concerns remain about the effects of these new technologies on issues such as privacy, equality and discrimination. Although the tensions between the competing demands of Big Data advocates and their critics may appear irreconcilable; only by highlighting these points of contestation can we hope to begin to ask the types of important and difficult questions necessary to do so, including; Big data is going to be a big business, in India in coming years which means ignoring them is not going to be a healthy decision. It will not be wrong to posit that the more you learn about your customers the better you will be able to target them with your social media campaign, and seeing the gigantic size of data produced by various social channels, it becomes imperative that you make use of big data in your social media marketing campaigns. By giving you a far deeper understanding of your customers and their relationship with your brand, big data will help you fine tune your social media messages, and choose the right social media platform to disseminate information.

5. References

[1] Meeker, M. & Yu, L. Internet Trends, Kleiner Perkins Caulfield

Byers, (2013),http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013 .

[2] Joh. E, 'Policing by Numbers: Big Data and the Fourth Amendment', Washington Law Review, Vol. 85: 35, (2014)

https://digital.law.washington.edu/dspace-law/bitstream/handle/1773.1/1319/89WLR0035.pdf?sequence=1

[3] Raghupathi, W., &Raghupathi, V. Big data analytics in healthcare: promise and potential. Health Information Science and Systems, (2014)

[4] Anderson, R., & Roberts, D. 'Big Data: Strategic Risks and Opportunities, Crowe Horwarth Global Risk Consulting Limited, (2012)

https://www.crowehorwath.net/uploadedfiles/crowe-horwath-global/tabbed_content/big%20data%20strategic%20risks%20and%20opportunities%20white%20paper_ risk13905.pdf

[4] Kshetri. N, 'The Emerging role of Big Data in Key development issues: Opportunities, challenges, and concerns'. Big Data & Society (2014)http://bds.sagepub.com/content/1/2/2053951714564227.abstract, [5] Tene, O., &Polonetsky, J. Big Data for All: Privacy and User Control in the Age of Analytics, 11 Nw. J. Tech. &Intell. Prop. 239 (2013) http://scholarlycommons.law.northwestern.edu/njtip/vol11/iss5/1 [6] Newell, B, C. Local Law Enforcement Jumps on the Big Data Bandwagon: Automated License Plate Recognition Systems, Information Privacy, and Access to Government Information. University of Washington - the Information School, (2013)

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2341182

[7] Morris, D. Big data could improve supply chain efficiency-if companies would let it, Fortune, August 5 2015, http://fortune.com/2015/08/05/big-data-supply-chain/

[8] Davenport, T., Barth., Bean, R. How is Big Data Different, MITSloan Management Review, Fall (2012), Available at, http://sloanreview.mit.edu/article/how-big-data-is-different/

[9] United Nations, A World That Counts: Mobilising the Data Revolution for Sustainable Development, Report prepared at the request of the United Nations Secretary-General,by the

Independent Expert Advisory Group on a Data Revolutionfor Sustainable Development. (2014), pg. 18, see also, Hilbert, M. Big Data for Development: From Information- to Knowledge Societies (2013). Available at SSRN: http://ssrn.com/abstract=2205145

All the pictures that you share, all the smiley that you post, all the videos that you shares, all your likes, comments, and shares, tweets, blogs, videos, posts, links, data from GPS signals, etc., adds up to 2.5 quintillion bytes of data every day.

Is it a good or a bad news?

Like everything else, it depends on how you take it. Big data can be a boon for business (and also for social media campaign) if harnessed effectively, but if it is not used to its capacity, collecting it, storing it, and maintaining it can be a very, very expensive affair. To help you understand its business use, an example of the way eBay uses big data should be sufficient. eBay uses big data for search, merchandising, and customer recommendation using 90PB data on consumer transactions and behavior on its websites across the globe. The shopping giant stores the data on 3 systems: in 7.5PB and 40PB warehouses, and 40PB in commodity Hadoop. The company is using big data to build a customer-friendly shopping ecosystem to assist its customers buy the things they want.

How does it affect social media?

As pointed above, big data is a massive collection of data from various sources (variety) coming at various speed (velocity), and in various quantity (volume), and social media websites are collectively responsible for adding massive chunk of data of all three kinds to the big data pool. But unlike other data sources, information produced and collected by social media websites are unstructured, and it is so enormous in volume that it is not humanly possible to collect, process, and manage such a huge set of unstructured data. It even falls out of range of commonly used software applications. But the scenario is not all that bleak. There are tools to help you make

sense of onslaught of messages sent to and fro on various social media platforms by bringing all together and providing a structure to it, and making it useful for marketers.

If you want to get a glimpse of how confusing it can be, go through a twitter feed of any popular brand, and also to its Facebook page among other social profiles (variety in big data) should you wish to be more confused, and then try to make sense of this all from a marketing point of view. And here we are just talking about making sense of an instance of spontaneously generated, untagged, and uncategorized data churned out. What will it be like if we factor in all the data which was generated before now, which will generate hence forth! Add to this the data being generated now, as you read this, in real time (the velocity aspect of big data).

Some facts about big data and social media

1. Facebook takes in 500 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)

2. Twitter produce 12 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)

3. Facebook tracks every computer IP a user has logged in from, and other users who have logged before and after you from the same computer up to 800 pages size of data per users. (Source: com)

4. More than 4 Billion hours of videos are watched on YouTube each month. (Source: IBM Big Data Hub)

5. More than 30 billion pieces of content is shared on Facebook each day. (Source: IBM Big Data Hub)

6. By 2016, there will be 18.9 billion network connections, i.e., 2.5 connections per person. (Source: IBM Big Data Hub)

How big data helps in social media marketing

In the wake of changes brought in by big data, a brand needs to stop hiring a college student and fresher to curate its twitter feed or Facebook timeline, or any of its social profiles, for that matter. The brand also needs to stop guesstimating the future course its prospects and consumers will take and waste money based on that. Instead a brand should look for more and more data on its customers and prospects, other than what they share with you through their various interactions. In this, big data can help you a great deal. It can help you find out:

 Who buys from you?

This is as relevant as relevancy goes. In order to build a relationship and foster loyalty, the first and foremost thing you need to know is who is your customer, and that too not only in the demographic sense as suggested by market segmentation strategy of yore. Market segmentation

is not sufficient anymore. Now you need to know more about your buyers’ preferences, places they hang out at, the things they talk about, the issues they are concerned with, the topics that excites them, etc., to target messages better on social media.

 How your customers feel?

It is not just the customers’ life that you should be interested in. In order to make your messages more useful for your brand and your customers you also need to gauge customers’ sentiment around your brand and your competitors. Big data can help you understand your customers’ sentiment about your brand as well as your competitors.

 What they want?

This is one thing every brand tries to get a definite answer of. And I am not saying harnessing big data can give you a definite answer, but it will give you a much clearer picture of your customers’ needs and wants than you can get from any other source. By tapping into their interactions, things they talk about, things they say, products they buy, and places they visit, etc., big data can be help you estimate your customers’ demand.

 How do they satiate their information need?

By harnessing big data you can know a great deal about how your customers get the information they need. An understanding of the information sources your customers use to seek information you need, you can wisely select the vehicle to send your marketing message, and fine tune your message to match the vehicle and mood of your customers.

 How do they arrive at the buying decision?

The most important information a marketer wants is the knowledge of the process its customers took right from the 1st stage in the buying cycle; from gathering information to shortlisting product options to evaluating alternatives to shortlisting items to buy from to finally making the decision, and then its post-purchase interaction with the brand. This is a gold mine of information, and an access to it will help a marketer fine tune its social media marketing campaign at each stage of customers’ buying cycle.

3. Scope of Study

Interlinking Information Technologies via Linked Data Information Technology connections

Linked data technologies are used as information infrastructure for integration of data from disparate sources. Comparing to mainstream technologies of relational databases, linked data technologies have advantages in cases where relational databases demonstrate slow performance and inefficacy, namely integrating (joining) data about a certain object. Another advantage of linked data technology is its ability to automatically integrate data from RDF database with data

from external sources like web data or sensor data, etc. Linked data could provide structure (RDF triples) and metadata to unstructured data like textual data or several data streams. At the same time, most RDF databases have currently slower performance (except join operation) than most commercial relational database systems. However, there are good commercial RDF datastores available (AllegroGraph, Big OWLIM, Marklogic, etc.) and also open source RDF database systems like Virtuoso, 4store, Bigdata etc. Comparing to web services technology that also enables to create data-integration services, linked data technologies are lighter, more flexible, faster and as such cheaper. Linked data technology is built on existing web standards (and open source RDF stores) that enables small and medium size companies to use it for development of data integration solutions. They might not have resources for building data integration solutions based on web services technology.

Fig: Interlinking Information Technologies via Linked Data

In the following Fig , most important connections of linked data technology with other information technologies considered in this paper are depicted. In addition, the figure also shows relationships between these other technologies.

 Big Data explosion is driven mainly by the following technologies:

 IoT that provides various sensors and connected devices collecting data about environment or human activities

 Social web generating a huge amount of data (e.g. audio, video, click-streams, etc.) by different online activities. In addition, social web networks share a huge amount of data of different types.

Linked data technologies play a central role of integrator of other technologies. Link data technology provides tools for the following types of data processing:

 Data fusion

 Structuring of semi- or unstructured data  Providing of semantic metadata

 Linking of data

 Usage of common web standards for representation of data (e.g. RDF) and metadata or vocabularies (e.g. OWL).

Other technologies like Big Data, social media and IoT can benefit from applying linked data technology tools for processing collected data and developing new innovative applications. In the following subsections, linked data connections with each of analysed technologies are examined in more detail.

4. Conclusion

Today Big Data presents us with as many challenges as it does benefits. Whilst Big Data analytics can offer incredible opportunities to reduce inefficiency, improve decision-making, and increase transparency, concerns remain about the effects of these new technologies on issues such as privacy, equality and discrimination. Although the tensions between the competing demands of Big Data advocates and their critics may appear irreconcilable; only by highlighting these points of contestation can we hope to begin to ask the types of important and difficult questions necessary to do so, including; Big data is going to be a big business, in India in coming years which means ignoring them is not going to be a healthy decision. It will not be wrong to posit that the more you learn about your customers the better you will be able to target them with your social media campaign, and seeing the gigantic size of data produced by various social channels, it becomes imperative that you make use of big data in your social media marketing campaigns. By giving you a far deeper understanding of your customers and their relationship with your brand, big data will help you fine tune your social media messages, and choose the right social media platform to disseminate information.

5. References

[1] Meeker, M. & Yu, L. Internet Trends, Kleiner Perkins Caulfield

Byers, (2013),http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013 .

[2] Joh. E, 'Policing by Numbers: Big Data and the Fourth Amendment', Washington Law Review, Vol. 85: 35, (2014)

https://digital.law.washington.edu/dspace-law/bitstream/handle/1773.1/1319/89WLR0035.pdf?sequence=1

[3] Raghupathi, W., &Raghupathi, V. Big data analytics in healthcare: promise and potential. Health Information Science and Systems, (2014)

[4] Anderson, R., & Roberts, D. 'Big Data: Strategic Risks and Opportunities, Crowe Horwarth Global Risk Consulting Limited, (2012)

https://www.crowehorwath.net/uploadedfiles/crowe-horwath-global/tabbed_content/big%20data%20strategic%20risks%20and%20opportunities%20white%20paper_ risk13905.pdf

[4] Kshetri. N, 'The Emerging role of Big Data in Key development issues: Opportunities, challenges, and concerns'. Big Data & Society (2014)http://bds.sagepub.com/content/1/2/2053951714564227.abstract, [5] Tene, O., &Polonetsky, J. Big Data for All: Privacy and User Control in the Age of Analytics, 11 Nw. J. Tech. &Intell. Prop. 239 (2013) http://scholarlycommons.law.northwestern.edu/njtip/vol11/iss5/1 [6] Newell, B, C. Local Law Enforcement Jumps on the Big Data Bandwagon: Automated License Plate Recognition Systems, Information Privacy, and Access to Government Information. University of Washington - the Information School, (2013)

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2341182

[7] Morris, D. Big data could improve supply chain efficiency-if companies would let it, Fortune, August 5 2015, http://fortune.com/2015/08/05/big-data-supply-chain/

[8] Davenport, T., Barth., Bean, R. How is Big Data Different, MITSloan Management Review, Fall (2012), Available at, http://sloanreview.mit.edu/article/how-big-data-is-different/

[9] United Nations, A World That Counts: Mobilising the Data Revolution for Sustainable Development, Report prepared at the request of the United Nations Secretary-General,by the

Independent Expert Advisory Group on a Data Revolutionfor Sustainable Development. (2014), pg. 18, see also, Hilbert, M. Big Data for Development: From Information- to Knowledge Societies (2013). Available at SSRN: http://ssrn.com/abstract=2205145