Purchase And Implementation Of A Big Data Analytics Package For Intelligent Information Inc

Background

This project is based on the purchase and implementation of a Big Data Analytics package for Intelligent Information Inc that will enhance the existing business operations and marketing policies of the company (Marz and Warren 2015). The implementation of the Big Data Analytics Package has been suggested by the CIO due to a number of reasons. Firstly, the Big Data Analytics Package will be able to provide an integrated platform on which all the various required operations from different stakeholder groups can be performed all at once. This will replace the need for separate platforms for each department that are not only hard to manage but also have too much maintenance and management costs (Wamba et al. 2015). Secondly, with the new analytics platform almost of the operations will become automated and not further require too much human interference. This will also reduce the operational errors caused by the manual management systems.

Project Background

The CIO of Intelligent Information Inc wants to deploy a suitable big data platform that will help various stakeholder groups of the company. Some of the important requirements include identification of potential customers, improvement of service, management and maintenance of IoT sensors, fraud detection and prevention and others (Dhamodaran, Sachin and Kumar 2015). The main challenge of the development is that all of the requirements should be met such that all of these should be integrated within one common platform. In other words, there should not be separate systems for the different requirements; there will be one common platform through all of the required operations can be performed. 

Project Scope Statement

Based on the background and requirements of the project, the project scope can be determined as follows.

Scope 1 – Purchase and implementation of a Big Data Analytics Package is within the scope of the project.

Scope 2 – Integration of all stakeholder groups is within the scope of the project.

Project Objectives

The objectives of the project are as follows.

• To hire a suitable consultant for helping to identify best analytics package
• To recruit project team consisting of technical experts
• To procure sufficient budget for the project
• To deploy the new Big Data Analytics Platform
• To train the existing employees to use the system

Implementation Plan

Work Breakdown Structure

The work breakdown structure of the project is as follows.

Figure 1: Work Breakdown Structure of the Project

(Source: Created by Author)

Project Schedule

The estimated project schedule is shown in the following table.

 Project Budget

The overall budget of the project is estimated as follows.

Risk Management Plan

The risk management plan for the project is developed using risk register matrix as follows.

The stakeholder register for the project is developed as follows.

Project Scope

In order to develop an appropriate stakeholder management strategy, an RACI matrix is developed as follows.

Furthermore, as per the stakeholder management strategy, each stakeholder must follow the following guidelines.

Communication – The stakeholders must communicate with each other via appropriate medium throughout the project.

Cooperation – The stakeholders must cooperate with each other throughout the project (Kerzner and Kerzner 2017).

Performance – The stakeholders must exhibit maximum enhanced performance throughout the project.

Adherence to Policy – The stakeholders must stick to company guidelines and policies at all situations.

Conclusion

In this report, an initial project plan has been developed for the proposed implementation plan of the Big Data Analytics Package for Intelligent Information Inc. As per the estimated plan, the overall project duration is around 6 months and the estimated budget for the project is $1,500,000. As per the proposed plan, ten different internal and external stakeholders have been appointed for the project who will manage various aspects of the same. 

References

Dhamodaran, S., Sachin, K.R. and Kumar, R., 2015. Big data implementation of natural disaster monitoring and alerting system in real time social network using hadoop technology. Indian Journal of Science and Technology, 8(22), p.1.

Fleming, Q.W. and Koppelman, J.M., 2016, December. Earned value project management. Project Management Institute.

Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), pp.137-144.

Harrison, F. and Lock, D., 2017. Advanced project management: a structured approach. Routledge.

Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A. and Khan, S.U., 2015. The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, pp.98-115.

Heagney, J., 2016. Fundamentals of project management. AMACOM Div American Mgmt Assn.

Kerzner, H. and Kerzner, H.R., 2017. Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons.

Marz, N. and Warren, J., 2015. Big Data: Principles and best practices of scalable realtime data systems. Manning Publications Co..

Schwalbe, K., 2015. Information technology project management. Cengage Learning.

Walker, A., 2015. Project management in construction. John Wiley & Sons.

Wamba, S.F., Akter, S., Edwards, A., Chopin, G. and Gnanzou, D., 2015. How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, pp.234-246.

Wang, Y., Kung, L. and Byrd, T.A., 2018. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, pp.3-13.

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