big data services, marketing challenges of big data services. .... emerging services in big data analytics and its derivatives are presented below. 1) Measuring ...
Marketing Challenges for the Emerging Services of Big Data Technologies and Solutions Sasmita Mohanty, António C. Moreira Department of Economics, Management and Industrial Engineering, University of Aveiro, Aveiro, Portugal, 3810-074 Abstract – Big data is no more a jargon for the people, because it is ubiquitous now. It has become a business reality, though its challenges are too complex to be handled by the traditional systems. Big data management is a great challenge for the people and companies who deal with it. There are several new services emerging from the big data management. The emerging services are very much new. Their effective provisioning and marketing are very much different from the existing services. There are few solutions and technologies emerging for big data related problems and complexities. However, its marketing and business proliferation is still very much unknown. The marketing challenges are very much tough, and out of the present solution domain. In this work, we provide the emerging services in the big data management and their marketing challenges and options available in the present framework. Keywords – Big Data, big data management, marketing of big data services, marketing challenges of big data services.
I. INTRODUCTION Big data management is a huge field and it has many ramifications depending on the applications, utilities and storage. There are also secondary perspectives such as the cost factors associated and the profits incurred in the processing of the big data. This area has several new services on offer. Most of these services are different from the usual services of the information technology (IT) industry. Emerging services of big data management are quite new and face several challenges for their marketing. This is the age of big data. With the growth and proliferation of internet in different forms data is generated and utilized wherever there is human activities and smart environment. The growth of data is really huge and the trend of growth is also miraculous. Businesses face a challenge to collect their meaningful data and to utilize them in their own favor. It is clear that the companies and business cannot manage (and thus cannot use to their favor) the data which they do not measure. In order to measure the big data, there are huge problems from both the technological and management perspectives. This paper addresses these challenges and the initiatives taken for the popularization and marketing of those emerging services of big data.
II. THEORETICAL BACKGROUND ‘Big data’ is a jargon in the software engineering, information technology and database management. However,
now it has crossed all the barriers and became a common phrase in science, technology and management. It normally represents the voluminous amount of data produced by various means and mechanisms without a proper structure or class or size or orientation or different combinations of these. Thus ‘big data’ is quantified by the four dimensions (volume, velocity, variety, and veracity, also known as four Vs) in the current industry standards set by the big players like IBM and Google. However, big data is a relative term and depends on the context of its application and storage. But in a general sense, for a layman, big data is really big. It is not the kind of data that we process in our personal computers using the widely available software. It is the huge amount of data stored in gigantic storage facilities. The amount or size of the data is so big that the presently available software tools are not able to process it. It needs special facilities and special technologies for their analysis and trending. In the following subsections we clarify some of those issues.
A. Big data generation The internet users today know how the data is created and utilized. The webpages, emails, online chats, tweets, social networking profiles and photos, mobile phone records, SMSs, video clips, video streaming over the internet, software logs, all contribute to the big data. But, that is not all. Big data created by the humans is just a fraction of the net big data in the world. A larger part of the big data is created by the machines and sensors. For example, the ATMs which deliver cash of worth billions of dollars equivalent, the flight data recorders which keep the readings of all flight information, the observatories which keep the records of heavenly bodies round the clock, the stock exchanges which record the millions of transaction details, millions of CCTV cameras capturing the moves of the surroundings and interiors, the healthcare system which monitors the patient details in different formats, billions of transactions done by the supermarkets across the world through their electronic retail machines, all contribute to big data. The net amount of information created and consumed in the world is really huge. According to the HMI Report, the amount of data consumed in the world in 2008 was 9.57 zettabytes or 9.57 × 1021 bytes. United States is the largest consumer of that data. The largest fraction of the global data is found to be video and pictures. However, the net stored amount of data in various databases is found to be 1.9 zettabytes. According to the recent reports of IBM the net amount of stored data per day is of the order of 2.5 × 10 18 (or
2.5 quintillion) bytes. The rate of generation and consumptions are growing rapidly due to the increase in the number of sensors, user devices, population and the processing speeds. B. Storage Storage of the data is the first step to increase its utility. Storage of data in case of individuals may be simple. But for the storage of big data and its derivatives it is a great challenge. The companies that handle big data use data banks and gigantic data centers to keep those data. Google has more than 1 million servers to store its data. Similarly, Facebook, IBM, Amazon, Microsoft and other big players too have their own data centers to store the data. C. Processing of big data Processing of big data is a new challenge for the technologists. In the traditional data processing, the memory required was not too big and the existing database management tools were enough for the analysis and processing. But, for big data there is no technology at hand. The requirements are not known to many database management engineers. The common processes of big data management are described briefly. 1) Searching Searing is a basic need for the proper utilization of big data. If the data cannot be searched then their components and constituents cannot be retrieved and used for various purposes. The search processes used in the PCs and other common computing platforms are not very fast and effective. Also their workspace is limited to few hundreds of gigabytes. But for big data search process the machines have to use fast processing systems with great speeds and memory management technologies. The search algorithms are to be fast and effective as well. 2) Cataloging and classification Cataloging is a common requirement in big data management. With proper cataloging the data can be classified properly and thus its utility increases by many folds. Cataloging of big data needs a lot of parameters to be measured and processed. The memory requirements and the back end supports are also huge. Cataloging of big data also faces big challenges from the networking aspects. As one machine cannot do all the analysis, the data are to be analyzed simultaneously in parallel over several machines and those machines need to interact with each other to do the things effectively in tandem. So, fast interconnections with high bandwidth are needed for this process. 3) Indexing Indexing of big data is a basic operation for making the data systematic. Indexing helps in the trending and searching. With proper indexing the big data complexities are reduced by many folds. Indexing allows a lot of flexibility in the
storing and retrieval of data when needed for different processing aspects.
III. METHODOLOGY We study the cloud and big data management initiatives of the big players such as Google, IBM, Microsoft, Facebook and Amazon for this work. We went through specific steps taken in this aspect by these companies. Out of those steps we select and study the emerging services of the big data arena and their marketing challenges. Cloud initiatives are very much clear as the companies announce their foresight over the growth and future focuses. But much more deep analysis is needed to understand the challenges and solutions associated with the big data emerging services.
IV. EMERGING SERVICES IN BIG DATA MANAGEMENT There are several services emerging from the big data management. Big data itself is also seen as a service to many experts and organizations. But that big data would be useful only after it is properly classified, processed to be fit for different uses and measured accurately in terms of its utility parameters. So there are some essential services needed for the big data management and utilization. We provide some of the main services, which play the main roles in this area and essential for the operations of the big data management. A. Big Data Analytics Big data needs a lot of processing and analysis to be usable by the companies and nations. For that there are some tools which can provide quite meaningful insights on the big data that the companies hold or looking to analyze. Most of the big data efforts are now focused on analyzing internal data to extract insights and trends. Analytics provide a clear insight of the data available and the actionable steps that can help the organization get the maximum output from it. Recent emerging services in big data analytics and its derivatives are presented below. 1) Measuring the data and its potential Every company or organization first need to measure the data they have to exploit its full potential. Without measuring the data the management is not possible. The measurement metrics and standards are not there for the big data. This is the very basic service the companies need to do in their data centers and clouds. 2) Security aspects of the cloud and big data With the increase in the amount of data, the security of data has increased significantly. Now there are many types of security warnings for big data. Hacking, frauds and many other malicious threats are the potential dangers for the data centers. Security is thus a very basic service for the big data management.
3) Improving Operational Efficiency Operational services are the key to the big data processing. Operational efficiency in needed in several fronts for the effective and affordable big data analysis. With the current operational efficiency is not possible to process the gigantic big data. First of all, a huge storage is required where the data can be kept is a proper hierarchy and can be retrieved easily when needed. The memory requirement for big data is also enormous. Above all excellent parallel processors are needed for effective operations. 4) Increasing revenue generation potentials Big data is big in size and the returns from its possession and effective uses are also expected to be huge. Big data provides excellent business intelligence. Companies mainly aim to exploit the intelligence of the data they possess to make it a revenue generator. Raw and unprocessed data does not provide any intelligence or revenue. Accurate measurement and dimensioning gives meaning to the unstructured data. 5) Reducing risks and failures Several risks are there in the big data management and processing. The risks are both internal and external. Internal risks, however, can be managed by proper planning and implementation of the systems. But the external risks are unpredictable and needs protections all the time. 6) Implementation of new business models Big data management front also demands the changes in the management aspects. Big companies such as IBM and SAP provide different business models for big data management. There are also new initiatives to merge several technical aspects in the management to make the things smoother for the mangers. 7) Privacy of the cloud and the big data Privacy is a basic need in data management. In every electronic system, the privacy settings and service provisioning play pivotal roles. The social networks and other data driven companies provide privacy to their users. In the hostile environment of several attacks on the data centers and clouds, privacy provisioning is a key service.
V. MARKETING CHALLENGES IN BIG DATA RELATED SERVICES Marketing is a basic need for the service providers to get attention, recognition and invitation from the clients. Big data related services face big challenges in marketing. The main reason is that they find it very difficult to hit the target at the right time and place. The common advertising related marketing does not make a big impact in their efforts. Of course IBM has taken bold steps in this regard. IBM now poses it as the main player for big data management. It is clear from their logo saying ‘smarter planet’. In fact, the smarter planet initiative is nothing but the phrase showing
IBM’s expertise in managing big data. Big data marketing faces the biggest challenge from within. The big data owners are facing troubles in making the services popular and understandable for the target audience. A. Novelty of the Services Big data services are very new and there are not too many service providers. The jargons and semantics of big data are not understandable by the common man and the big spending in the traditional media does give the expected results. There is a need to address the issues through the technical platforms such as the social networks, public shows and talks like TED. B. Difficulties with the Traditional Marketing In the traditional marketing over different print and electronic media, big data does not get the target audience as the general readers do not comprehend its meaning. Of course in the specific high tech journals and magazines it gets some audience but that community is quite small. The most effective marketing for big data services are now the technical conferences and consultations. All the big players are doing the same at the moment. There is a need of a different strategy to market these new services.
VI. DISCUSSION Cloud computing and big data management are the two main aspects of the big players who do their business in the information technology and data management. Cloud computing is an emerging solution now for the big data management. Clouds are the local data clusters for the local demand and it reduces the load on central servers. It is understandable to a larger lot than big data. Clouds are advertised through the existing services (such as Gmail, Windows Live etc.). So its marketing is much easier than big data as it is localized and thus limited to local clients. However, this is just the beginning of big data related business management; many more complexities are yet to be addressed. Effective data management and business intelligence from these data are important for every company. It has become tough for the service providers to deliver services of high quality and reliability. IBM is the singled out player in the present emerging services in big data. It has both the talent and management abilities to perform the analytics and manage the data in effective ways. However, the challenges are increasing with the exponential growth of the data generated by the individual users as well as the businesses.
VII. CONCLUSIONS Big data management is a challenging technology sector and the revenue associated with it is huge. Its future growth potential is very strong as the amount of data will keep increasing and their effective management is quite essential. This work is based on the study of five dominant players of big data management. This work is done to acknowledge the
business potentials of big data and its importance in new emerging trends. The emerging services in big data management are very much novel. The service providers are also quite limited in number and the clients are very much dependent on the recent innovations in this area. Except a few, most of the services in big data management are yet to be solved. The advertisements presented in the media are not very effective in impacting the target audience. Novel techniques are needed for big data management and marketing.
frontier for innovation, competition, and productivity, McKinsey Global Institute.
The emerging services in big data are great challenges for the service providers as well as the service marketers. Most of the services are intangible though the performances can be evaluated easily by various methods. More research and innovation initiatives are being taken for the proper management and meaningful use of big data. Similarly the marketing ideas of the concerned services too are getting better. But the marketing aspects of the big data management will remain tough for the marketing teams of the respective service providers for some years.
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