Big Data Challenges and Opportunities – Case Study Example
System Analysis and design McCafferty, Dennis. Staggering Revelations about Big Data. Baseline Magazine, January 29, Available at: http://www.baselinemag.com/cloud-computing/slideshows/staggering-revelations-about-big-data (Accessed: April 16, 2015).
The growth of big data continues to amaze, when its potential is considered. Only 0.5% of the existing world’s data has been analyzed, meaning that there is an enormous amount of data that still needs to be ventured into. However, it is worrying that with the huge potential for the un-extracted data that requires being analyzed, the IT professional potential continues to decline. According to the article, it is expected that the current number of IT professionals globally will have reduced by 1.5 times by 2020. This simply means that the potential for extracting and analyzing the existing data that has not been extracted continues to dwindle. This therefore means that it may never be possible to take advantage of the existing business potential still locked in the un-extracted data, unless more training of IT professionals is done. Therefore, the article serves as an eye opener on why there is a need to develop more IT professionals than what is currently happening globally.
McCafferty, Dennis. Innovative Analytics Boosts Organizational Edge. Baseline Magazine, April 15, 2013. Available at: http://www.baselinemag.com/analytics-big-data/slideshows/innovative-analytics-boosts-organizational-edge (Accessed: April 16, 2015).
There is a great need for organizations to venture more into data analytics as a source of their competitive advantage. According to the article, only 19% of the data analytics-challenged organization identifies their customers using data analysis. This therefore means that there lays a great potential for improving business performance for most organizations, through adapting data analysis as the fundamental basis of identifying the target customer needs, and then designing the means of achieving them. Further, even for the data analytics innovators, only 38% uses data analysis to enhance their customers’ experiences entirely or most of the times, while the same is lower for the data analytics-challenged organizations at only 13%. This results in the development of the opinion that there is a great potential for data collection and use by business organization, which then requires to be exploited.
Greengard, Samuel. Big Data Challenges and Opportunities. Baseline Magazine, May 17, 2013. Available at: http://www.baselinemag.com/analytics-big-data/slideshows/big-data-challenges-and-opportunities (Accessed: April 16, 2015).
Data mining potential and strategies have greatly increased in the past years, and thus currently, 1800 Exabyte of data is generated annually globally. However, the major problem is on how business organization and even government institutions can transform this huge data into actionable information, which can then deliver business benefits for such organizations. Thus, while the major problem in the past has been the accessibility of data for most organizations, the current problem is that there is too much data accessible by organizations, but such organizations do not know how to transform that data into useful information. Thus, the data mining technology has developed fast compared to the data analysis technology. This therefore requires that more investment is done in data analysis, to make data analysis easier and understandable. This will then enable organizations and government institutions to take advantage of the existing hue data potential, and convert it to useful busyness information.
McCafferty, Dennis. Nine Companies That Built Success on Business Data. Baseline Magazine, June 24, 2013. Available at: http://www.baselinemag.com/analytics-big-data/slideshows/nine-companies-that-built-success-on-business-data (Accessed: April 16, 2015).
The advantage that data analysis and application has for business is not limited to any particular industry, business or business type. The difference between businesses that succeeds in taking advantage of data and those that do not achieve a great impact on transformation of the business lays in how well the business is able to utilize the data accessible to it. This forms the opinion that data accessibility is no longer the major problem for business organization, but rather data analysis. Thus, if business organizations are to take advantage of data analysis to enhance their performance, there is no doubt that such business must not only be committed to invest in appropriate data analysis technology, but also in competent data analysis personnel. Thus, if any business or government institution is to become successful in its performance, the investment in data analysis technology and competent data analysis personnel is no longer an option.
McCafferty, Dennis. Companies Face Hurdles in Pursuit of Analytics. Baseline Magazine, July 4, 2013. Available at: http://www.baselinemag.com/analytics-big-data/slideshows/companies-face-hurdles-in-pursuit-of-analytics (Accessed: April 16, 2015).
Data collection has increasingly become easier for businesses, but its evaluation is the major hurdle. While the data mining and data analysis tools may be accessible to businesses, the major challenge in taking advantage of the existing data for business success lays in the inability of business organizations to customize the data analytics tools to their own data needs. One thing that is clear though, is that data analytics will definitely become a source of business competitive advantage in the future. What organizations needs therefore is investment in competent leadership that can lead the organizations towards data analytics application. Further, business organizations must now develop ways of converting the easily accessible data into their own information application, which can enable them use such data to increase sales or identify more business opportunities. The secret lay in developing data analytics tools that can be customized for individual organization’s data analysis needs.