BIG Data: An Enabler in Developing Business Models in Cloud Computing Environments

BIG Data: An Enabler in Developing Business Models in Cloud Computing Environments

K. Hariharanath
Copyright: © 2019 |Pages: 30
DOI: 10.4018/978-1-5225-3182-1.ch007
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The basic functions such as production, marketing, and finance continue to be the same from an agricultural economy to an industrial economy. Business processes, procedures, methods, strategy, management thinking, and approach related to basic functions have been changed due to global market competition. Consequent to global competition, business activities have become more complex. Due to this complexity, the type and quantum of information required by the business enterprises are increasing. It is interesting to note that information and communication technology is providing many new concepts to handle and manage the complex information to remain competitive in the global market. The concepts such as big data and cloud computing along with other collaborative technology facilitate creating conceptual business models for facing realities in the global market. This chapter mainly explains with two case illustrations of the importance of the above concepts for developing business models for textile and retail sectors.
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Globalization, which was initially viewed with fear and distrust has opened up huge new markets for many business enterprises across the globe. This has been focusing on the need for an innovative approach in conducting business by enterprises. It is apt to recall the observation of Peter Ducker on innovation. “A Business enterprise has two and only two basic functions, marketing and innovation. Marketing and innovation produce results. All the other departments are cost centers. The dividing factors in the market are niche markets and unique products or services. Innovative approach is needed to achieve the above factors in the present competitive market. Strategic thinking is required for any innovative approach. Strategic thinking decisions are based on the following:

  • 1.

    An understanding of the current and emerging needs

  • 2.

    An understanding of the organizations current and anticipated future core competences such as special skills or knowledge resources and culture and

  • 3.

    A future view of the industry sector and marketplace.

Even the most stable industries and the strongest brands can be blown to bits by the emerging concepts in information and communication technologies. Technology is forcing to rethink its business models and organizational designs as it contributes to the re-balancing of power in the market place. It is no longer guaranteed to those organizations that have the financial resources and size on their side. Smaller organizations that are fast and flexible can now outmaneuver the traditional large enterprises by employing new technology that enables them to deliver goods and services to their customers at a faster pace and lower cost (Kumar & Kumar, 2013).


Case Illustration

3G Textile Mill is one of leading textile mills in India. This Textile mill has been in the business over five decades. The unique aspect of this mill is that it is managed by a management team consisting of a President, Senior Vice President and Vice President who belong to three different generations. Their approach and decisions are based on their experiences, business insight and education.

Key Terms in this Chapter

Variety: In the present business scenario data comes in all types of forms.

Volume: Many factors contribute towards increasing volume streaming data and data collected from sensors.

Streaming Data: An analytic computing platform that is used to speed.

Big Data: The capability to manage a huge volume of disparate data, at the right speed and within the right time frame, to allow real time analysis and reaction.

Velocity: This means how fast the data is being produced and how fast the data needs to be processed to meet the demand.

Data Warehouse: A large data store containing the organization’s historical data, which is used primarily for data analysis and data mining.

Cloud Computing: A computing model that makes information technology resources such as servers, middleware, and applications available over the internet as services to business organizations in a self-service manner.

Conceptual Model: A conceptual model is a representation of a system made of the composition of concepts which are used to help people know, understand, or simulate a subject the model requirements.

Data Cleansing: Software used to identify potential data quality problems.

Private Cloud: A private cloud is a set of computing resources within the organization that serves only the organization.

Predictive Analytics: A statistical or data mining solution consisting of algorithms and techniques that can be used for both structured and unstructured data to determine future outcomes.

Variability: Along with the velocity the data flows can be highly inconsistent with periodic peaks.

Unstructured Data: Data that does not follow a specific data format.

Business Analytics: Business analytics is the combination of skills, technologies, applications, and processes used by organizations to gain insight into their business-based data and statistics to drive business planning.

Data Science: Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured similar to data mining.

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