Management of Big Data

Management of Big Data

Outline

Company Name: Thomson Reuters

Company Challenge: Management of Big Data

1. Executive Summary (Group)
2. Introduction

• Content management is not an easy activity for organizations
• Content management demands dedication and concerted effort to guarantee secure, up-to-date, and relevant accessibility to data.
• Strategies employed to manage a vast amount of content as well as data in an organization determine the success of the organization as it can solidify or break its stability.
• Thesis statement
  • In the era of the high emergence of new technology, taking advantage of massive data is a mandate and not an option of organizations to ensure that they remain competitive in the market, which is a situation faced by Thomson Reuters.
• Problem Statement
• Management and delivery of data is a challenge faced by Thomson Reuters
• This challenge affects the company’s formation of coherent strategies that should be undertaken at an executive level.
• The problem causes cost issues as much funds are spent to moderate its effects and solve the challenge.
• The management of data through aggregative, cleaning, as well as analyzing, has become extremely expensive.

  Don't use plagiarised sources.Get your custom essay just from $11/page

  GET CUSTOM PAPER

1. Effects Caused by The Challenge
   1. Effect 1 (Handling of a massive data amount)

• Huge data possess difficulty in handling as it eventually affects the success of Thomson Reuters.
• The company faces a severe challenge of storing and analyzing huge data.
• Management and retrieval of the data may be cumbersome as it exceeds the capacity to be stored and computed.
  1. Effect 2 (Security)
• Huge data causes risks in its security.
• Handling huge data makes the company expose information to a wide range of sources, which cannot be trusted to being compliant with the company’s standards and security.
• It may later lead to inconsistency of data.
• It is difficult to identify the compromise challenge, and this is a significant risk to security as much of the channels become compromised.
  1. Effect 3 (Shorted of skilled personnel to handle the data)
• The company faces a shortage of specialized Big Data expertise to manage its data.
• Lack of this professional affects effectiveness in the analysis and execution of the data in time.
• Lack of experience leads to difficulty in “number crunching.”
  1. Effect 4 (data Validation)
• Big amount of data affects the validation process as integration and analysis is compromised
• There is a huge conflict in the data available.
• Accuracy of the data is also compromised as many skills are required for computation.

1. Existing Strategies Set by The Company in Solving the Problem (Group)

1. Effectiveness of These Strategies in Solving the Problem (Group)

• New Strategies That the Company Can Adopt in Solving the Problem (Group)

• Conclusions and Recommendations (Group)

References

Enterprise Content Challenges: Q&A with Thomson Reuters’ Chief Content Officer. (2016, March 30). Seismic. https://seismic.com/company/blog/enterprise-content-challenges-qa-with-thomson-reuters-chief-content-officer/

Katal, A., Wazid, M., & Goudar, R. H. (2013, August). Big data: issues, challenges, tools, and good practices. In 2013 Sixth international conference on contemporary computing (IC3) (pp. 404-409). IEEE.

Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033.

Rabl, T., Sadoghi, M., Jacobsen, H. A., Gómez-Villamor, S., Muntés-Mulero, V., & Mankowskii, S. (2012). Solving big data challenges for enterprise application performance management. arXiv preprint arXiv:1208.4167.

Silverman, V. (2017). Thomson Reuters innovation case study. Strategic HR Review.

Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data challenges and analytical methods. Journal of Business Research, 70, 263-286.