Data A Analytics
[Name of the Writer]
[Name of the Institution]
Data collection and compilation has always been an important aspect of the history of organizations. Companies and organizations have always collected data using various useful methods and tried to gather meaningful data so that it can be used in the interpretation and analysis of varying trends in the market (Sagiroglu, & Sinanc, 2013, May). This process holds more importance in the lives of big organizations, where the number of people using their products or availing their services is a huge and large amount of data. Data collection and processing, hold much more importance in the case of the service sector like hotels and the banking sector. Many articles and reviews have been published at various forums that provide information about the use of data. One such informative articles is “Why It Fumbles Analytics” (Marchand, & Peppard, 2013).
The article under discussion, “Why IT Fumbles Analytics” discusses some important and very critical issues in the area of data collection and analysis, especially in big organizations. It is full of information regarding various data gathering techniques and how big companies process and use this data with the passage of time. Here are some of the most critical issues highlighted and some relevant lessons learned through this article.
Three Most Critical Issues Discussed in the Article
Although the article discusses many issues regarding the data collection and analysis of this data, there are some issues that more prominent than others and stand out clearly throughout the article. It seems clear that the authors want to put more focus on these issues and want a definite solution for them. All of these issues have been listed below:
Companies treat their data processing just like all the other IT projects.
Companies adopt orthodox or conventional methods to treat their data
Companies deploy technologies but do not know how to use them or operate them.
Organizations need to understand that data processing requires specialized tools and systems. Companies need to install the upgraded systems for this purpose and then also get training on how to use this technology, instead of experimenting with it.
Three Most Relevant Lessons Learned from the Article
Although the article discusses many issues present in the data collection methods or techniques of big organizations, there are some positive notes present in it as well. The article contains many valuable lessons that an IT expert or even a layman can understand. These lessons can benefit big companies or organizations and the professionals working in the area of information technology, to understand the nature of the data. Moreover, these lessons can greatly help professionals in the analysis and interpretation of the data appropriately.
Companies should put more focus on people instead of technology and they should be the main aim of the initiation of the products.
The companies should focus more on extracting and emphasizing on information as a way to gain value from this data, instead of exploiting it.
IT professionals and companies should start cultivating the culture of information sharing.
In a nutshell, it can be concluded that companies and organizations need to upgrade their systems that collect and analyze data. Moreover, the companies should also proceed towards the new and updated systems of data analysis, instead of using older, conventional methods. The article related to current information technology, published on Harvard Business Review, with the title, “Why IT Fumbles Analytics” highlights the same facts. In addition to this, the article also directs the businesspeople and owners of big companies to focus more on people instead of the IT structures. The companies should train and prepare the people for the system so that they can handle the data properly.
Marchand, D. A., & Peppard, J. (2013). Why IT fumbles analytics. Harvard Business Review, 91(1), 104-112.
Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In 2013 International Conference on Collaboration Technologies and Systems (CTS) (pp. 42-47). IEEE.
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