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20Jul

Big Data Assignment Help

Introduction

            Big Data is a business intelligence tool which is used for decision making on the Information Technology (IT) platform. With business intelligence system, the use cases are accessed for providing important data to build some information regarding functional operations in business organizations. In this report, the importance of Big Data intelligence is discussed alongside its support in IT processes. Moreover, the merging of structured and unstructured data is discussed for making effective and efficient decision making of business organizations.

Why Big Data Intelligence is important

Big Data is an analysis approach and is a process of measuring Volume, Velocity and Variety of data that comes into an organization and reaches unprecedented levels. For an organization either it is a small one or larger one, there may be needs to store huge amounts of data such as 2.5 quintillion bytes per year. Such data are really difficult to maintain and process using the traditional data processing application tools and thus comes the term “Big Data” (Simon and Shaffer 2001).

Depending on their database sizes, each company have to implement some way of data processing and maintaining method which is otherwise called as “Big Data”.

big data assignment help

Importance of Big data

  1. Businesses today are really competitive and challenging. Such business requires a best way to store and manage their huge amount of data. Thus, Big Data comes in hand as a tool or a approach which helps to store and manage the data in a better way than any traditional methods (Simon and Shaffer 2001)
  2. Big Data can analyse data, share, store, transfer, visualize and maintain the information privacy of the data.
  3. Big Data approach helps you to find out the questions which you don’t know what you want to ask.
  4. It helps to take a look at the company’s future, its growth and development, and the way it maintains the huge amount of data through three factors such as

Volume: The amount of data being stored everyday in the organizational database.

Velocity: This is measuring the speed of data processing.

Variety: There are different types of data to be managed such as Unstructured and structured data.

  1. It has advanced distributed processing capability, cost effective cloud storage effective environments, searching and analyzing very large and disparate data sets very quickly, etc are the advantages of the Big Data Approach.
  2. Big Data Intelligence analysis is mostly used in planning, budgeting, forecasting profit of the company, financial accounting areas.
  3. Most of the users of the Big Data Analysis say that they believe that this tool will improve their organizational performance by 41% over next three years.
  4. With the Big Data tool it is easy to handle even the unstructured data which is too difficult to interpret.

Big data and decision making

Big Data helps to take the decision faster, react in flexible manner and at as earliest as possible, make full proof decisions, and take ethical decision outside the box and so on. It helps to identify bad credit risks of a company. It helps in smart procurement management. In helps in all department tasks such as Budget planning and how much money needed to be invested on each department, cost allocation, credit, collection and billing, payroll and fringe benefits (Agosti 2010, p.225). It helps in other activities such as determining the optimal job candidates, indentifying new sales channel, determining optimal sales offers, faster price adjustments due to the changing markets and also helps to improve the employee’s retention.

Example for Big Data Intelligence

An International Telecom company which provides voice, data and internet based services to more than 6 million customers makes uses of Open text Big Data Analytics to manage more than 1 Tera Byte of data, 14 Databases with 160 tables every day. Now the company is able to manage their data very easily and also deal with other segments such as micro segmentation campaign, customer loyalty, contact optimization, customer matrix and so on.

The help of Big Data management in IT Process management

  The IT processes are identified as managing information system, communicational practices, advertisements and marketing of products and services through online mediums etc. With development of multiple resources from information systems, it is observed that planning and implication of new products of services into market is supported by Big Data management tools. The business environment and culture of workplace is obtained through IT processes of internal and external factor evaluation for business, In the evaluating and monitoring, the Big Data management system support users to achieve designed targets (Hurwitz.et.al 2013). It is understood that effective planning and implication of management information system and records will provide useful outcomes for employees who are working to such IT processes (Goleman, Boyatzis and McKee 2002). With advancement of tools and technologies involved in business, the products or services in business are accepted and rejected by consumers. It is noticed that people are adapting only those things which are highly efficient with comparison to other product in market and also available at lower cost. So designing such products and services need stringent strategy of marketing mix. Big Data management is accessed for managing such decisions and operations through use of information stored in Business intelligence system with instant actions (Ohlhorst 2013). With information management systems like MIS, CRM, ERP etc., the knowledge can be concluded in demanded information formats through research and development tools. Big Data management can be accessed for searching databases together through information which is planned and developed in form of effective business management system. The demand of customers can be fulfilled through mechanizing multiple information system in large business through Big Data management. It will provide access of all the databases for generating demanded information in a set (Agosti 2010, p.238).

            With advance technologies like cloud computing, social media connectivity of such databases and existing records at a common place, Big Data management can review information at common platform (Soares and Ghani 2010). With identification of data regarding products and services, the market gap can be covered through IT processes which can be better supported by Big Data management. While focusing to targets in business, it is noticed that changes to existing IT processes can be identified and proposed with the help of facts collected through Big Data management software applications. It helps in filtering essential information and minimizing burden of large store for mining. The efficiency in operational planning and development through product and service identification, the business system will have useful outcomes for users. With development of different characteristics and functions in business, the services will be given to access management plan (Agosti 2010, p.330). With generation of demand according to business objectives and profitability, management uses Big Data management tool in strategic decisions of investment. Through financial figures and responses of products, in the market, IT processes are supported by access, control and monitoring of different values. With observation of ongoing IT practices in business, the products and services are advertised on basis of facts and figures which are accessed through business intelligence system. Through designing and implication of product planning and launching strategy in business, the several changes and implication of business are strategized through advance management tools and technologies which are processed through IT processes (Amoako-Gyampah and Salam 2004, p.745). While taking decision on the basis of data and information which is stored in company databases, the business strategies are made according to demand of customer through IT systems. For accessing the need of business, various tools and technologies of MIS, CRM and other information system are practiced through Big Data management system (Amoako-Gyampah and Salam 2004, p.731). With involvement of standard policies and practices for effecting IT processes in information access, modification and control, the demand of business decisions can be effectively managed according to demand of customers. The Big Data management tools are accessing demand of users for better controls in decision making can be practiced according to strategic needs.

Merging structured and unstructured data for decision making

            The data is identified as facts and figures about some specific research and study. Through access of data some information can be made on researched content. In business organizations, unstructured data is identified as the facts and figures collected through primary resources which need evidence of correctness through different resources like business intelligence information which is also identified as decision making material. The structured content or information is observed essential for making some specific research about projects and functional operations (Liebowitz 2006). Through identification of content which is specifically identified in business decisions will require advancement of structure or format in which data are collected and stored in various forms on computer storage. With effective monitoring and controlling from business research and content suppliers, the information related to business decision can be effectively used. With structures data, some effective and useful information can be made which will be used for business decision making in multiple operations. Through observation of tools and technology regarding information storage, the formats of data can be structured through equations and algorithms. With practices involved in business decisions, the understanding of researched content is crucial so that structured information is merged in some specific formats and reports (Soares and Ghani 2010). The idea of generating project report will be useful for products and services to be marketed effectively. Through planning of business intelligence access through Big Data Toolkit, the unformatted or unidentified facts or figures can be effectively merged to well identified or useful information. Through merging the researched content from social media, search engines, primary resources like sampling etc., the management can take intelligent decisions regarding functional operations. With continues development and access of demanded information few decisions can be recorded for future use which can be accessed as it is in critical situations (Neff 2013, p.117). Through involvement of databases access technologies and systems, the Big Data Toolkit is providing knowledge of strategic research for different functional departments in company. It will access the necessary information regarding marketing, financial facts and figures, knowledge blogs and technologies and methods can be better practiced in business intelligence format through Big Data Toolkit. The business analysis and report generation is dependent to idea which can be accessed for sharing and securing data. Through analytical tools and operations in Big Data Toolkit, the research information can be merged in format of structures set of data (Neff 2013, p.123). In business organization some decisions are taken on the basis of data rather than personal decisions and experience. Business intelligence helps in making decisions regarding information population through data resources and mining. The set parameters and performance objectives are accessed for merging content of facts and figures. There are some standard and parameters for planning and designing different tools and technologies so that efficient actions can be taken for business management. Through actions involved in business, it is necessary to follow the standard parameters involved in Master Data Management. There are databases which are accessed according to demand of user for generating management decisions (Ohlhorst 2013). It is observed that certain changes can be practiced by involving management theories and strategies in business. By collecting the unstructured information in structured format, the development of business information system is necessary. To use the facts and figures from products and other services, it is essential to work on database management system and access controls. With identification of different tools of IT to represent researched information, it is necessary to improve facts and figures in user demanded format. With effective warehousing and mining applications like Big Data Toolkit, the raw or unstructured data can be used for decision making in multiple functions. With observation of management tools and resources, the facts can be collected for business decisions. The identification of various IT resources is required to user for making use of Big Data Toolkit. With planning of structuring unstructured data, the management information system can be implemented as business intelligence system through IT.

Conclusion

            This report is providing details of Big Data use cases in planning, implementing and controlling information which is required for planned objectives. The technologies of IT like social media websites of Facebook, Twitter, WhatsApp, search engines like Google and research blogs. The Use case models are designed and implemented for planning and development of functional decisions in business organizations. Through access of merging formats developed through IT is effective to merge all kind of data. With analytical options for data in Big Data, the customer requirements are fulfilled by labour.

References

Agosti, M 2010. Understanding user requirements and preferences for a digital library Web portal. International Journal on Digital Libraries. 11(4). Pp. 225-238.

Amoako-Gyampah, K. and Salam, A. F 2004. An extension of the technology acceptance model in an ERP implementation environment. Information & Management. 41(6). pp.731-745.

Goleman, D., Boyatzis, R. and McKee, A 2002. Primal leadership. Mass.: Harvard Business School Press.

Hurwitz, J., Nugent, A., Halper, F. and Kaufman, M 2013. Big data for dummies. N.J.: Wiley.

Liebowitz, J 2006. Strategic intelligence. Auerbach Publications.

Neff, G 2013. Why Big Data Won’t Cure Us. Big Data, 1(3), pp.117-123.

Ohlhorst, F 2013. Big data analytics. N.J.: John Wiley & Sons.

Simon, A. and Shaffer, S 2001. Data warehousing and business intelligence for e-Commerce. Morgan Kaufmann.

Soares, C. and Ghani, R 2010. Data mining for business applications. IOS Press. Vogiazou, Y., 2007. Design for emergence. IOS Press.

Williams, S. and Williams, N 2007. The profit impact of business intelligence. Elsevier/Morgan Kaufmann.