Introduction

            Technological advancement in the last several years have led to massive usage of data from users who have a variety of internet enabled devices. Data analysts are now faced with a new challenge of handling the big data available for the general improvement of lives. It is through this challenge that improvising of the current methods used is of utmost importance. The following paper is based on an annotated bibliography of facts, challenges and ways of improving the methods data analysts use while handling big data.

Facts

            Tsai, C., Lai, C., C, H., & Vasilakos, V. A 2015. “Big data analytics: A Survey.” Journal of Big Data. P. 511- 723. DOI: 10. 1186/s40537-015-0030-3. From this survey it is quite clear that the traditional methods of collecting, cleaning and compression are inefficient in the face of the big data of today world. The authors of the article based their survey on the available information about big data handling and found out analysts are struggling and in dire need of better methods. The fact that technology is in constant change creates a new challenge for the analysts who have to seek ways of keeping up. However, generally the world’s data handling methods are bound to improve with technology as they are also technologically based. Therefore in the end a solution will be found that will ensure the data collected is handled in an effective way that allows for improved information and technology services. In addition, the 21st Century has provided the world with new and better ways of communication which is the reason there is big data which will improve the lives of people if properly handled.

            Parise, S., Iyer, B. & Vesset, D 2012. “Four strategies to capture and create value from big data. Ivey Business Journal. P. 231 – 300. The authors of the article are adamant about understanding the demands of big data before delving into finding ways of improving ways of handling it. Performance management is one of the most important aspects of big data that requires a deeper understanding. To understand the performance management Parise et al (2012, p. 256) argue that pre-determined queries are of utmost importance as they set the foundation of the understanding. Another strategy is measuring the social data which is non-transactional. From this data it is quite easy to have a put into perspective the feelings and needs of the target market in marketing for instance. Socially, the big data is paramount in keeping tabs of the social aspect and provide government security agencies and opportunity of keeping the country safe.

            Mitchell, L. R 2014. “8 Big trends in big data analytics.” Computerworld. P. 01 – 20. The amount of in production from the technological advancement has necessitated data processing methods in the cloud. Through this way, analysts have the ability of analyzing data in large amounts and coming up with viable information that is essential to human living. Notably, the challenges faced have played an important role in the innovation of cloud processing methods that make the data analysis is effective and does not miss any important information. The methods are essential in creating an impression in the information technology industry that everything is under control. If for instance the analysts were still struggling to handle the big data, people with ill intentions such terrorists might find loop holes through which they would use to communicate their plans and launch attacks; this is one reason why handling big data is paramount to even the government in its activities of maintaining security.

Challenges

            Cai, L. & Yangyong, Z 2015. “The Challenges of Data Quality and Data Quality Assessment in the Big Data Era. Data Science Journal. 14, p. 2. Doi: http://doi.org/10.5334/dsj-2015-002. The authors of the above article are wary of the speed at which data is created which increases the need for analysts to deal with it in a timely manner. If this does not happen, there is a chance some crucial information might pass through without notification. The challenge of speed requires methods that are able to analyze data without necessarily the analysts’ manual input. Another challenge that analysts face is the different features that big data possess. The features are subject to changes that occur constantly (Cai & Yangyong, 2015, p. 2). Focusing on these challenges the issue of handling big data becomes a source of anxiety as stakeholders are worried at the inefficiency of the methods in use currently. In essence, the Information Technology (IT) industry is in a precarious situation with regards to big data handling.

            Jin, X., Wah, W. B., Cheng, X. & Wang, X 2015. “Significance and Challenges of Big Data Research.” Elsevier. P. 311 -430. The complexity of the whole systems has provided another challenge for analysts. First the issue with regards to big data is complicated enough; additionally the fact that technology is in constant change worsens the situations. Data analysts are therefore faced by a situation where they are required to take further training to take on the new challenges caused by the systems. The fact that data analysts accept the challenges is a step towards finding a solution as they are willing to take up necessary strategies to improve the situation. A deeper analysis of the complexity indicates that previously the analysts relied on trial and error methods which are no longer futile as the data analysis requires a definite method. Unfortunately, the changing aspect of technology provides a whole new challenge that necessitates the need to take up refreshing causes.

            Khan, N., Yaqoob, I., & Gani, A 2012. “Big Data: Survey Technologies Opportunities and Challenges.” Elsevier. 7(67): 67 – 89. In their article, Khan et al (2012, p. 69) suggests the security aspect of the data and the information acquired provides another challenge. The existence of the challenge is based on the fact that technology is ever changing bringing in different features that need time before they are fully understood. In addition the speed at which the data is exchanged has significantly increased making the analyst review their methods to match the new speeds.

Methods of Improvement

            Muller, H., Christoph, F. & Leser, U 2012. “Improving data quality by source analysis.” Journal of Data and Information Quality. 2(4): 245 – 300. Finding a way in which data that contains the same topic is exploited at the same time is one of the suggestion Muller et al (2012, p. 267). The developers and the data analysts would also seek ways through which they could work together to have a better understanding of the new features. In the process, the analysts would be aware of the features before the users start using them which would give them a better chance of handling big data. However, the situation requires a concerted effort of a majority of the stakeholders which might be an expensive affair. Irrespective of the expected expenses the strategy is expected to provide positive results with regards to big data handling. The challenges on the other hand would significantly reduce giving the analysts more time to focus on the actual data analysis activities.

            Gandomi, A. & Haider, M 2013. “Beyond the hype: Big data concepts methods and analytics.” International Journal of Information Management. 5(12): 788 – 900. The fact that dimensions in data analysis are independent of each other leading to changes everywhere is one dimension changes creates an opening to finding a solution. Analysts should focus on unstructured data as it forms the independent data dimensions which interestingly are largely ignored. The discoveries of new aspects of technology are playing an important role in ensuring the data analysts take care of their responsibilities effectively. In the end, the challenges that for some time have increased anxiety in IT industry will significantly reduce.

            Mauro, D. A., Greco, M., & Grimaldi, M 2015. “What is the Big Data? A Consensual Definition and  Preview of Key Research Topics.” AIP Publishing. The definition of big data by Mauro et al suggests that there is ambiguity that allows for the inclusion of several aspects such as storing and aggregation of a huge amount of data. Through the definition arises suggestion of improving the current methods of data analysis which focus on placing importance on storing the data collected. The fact that big data has had both positive and negative impacts on the society asserts the importance of proper handling of the data as it might change the course of societies. It is in this sense that analysts are asked to keep up with the changes that are associated with big data. In essence, the analysts should focus on information, technology, methods and impacts of big data which will provide insights on proper handling methods compa