Q2. What have the authors stated for future works in "Big data analytics: understanding its capabilities and potential benefits for healthcare organizations" ?
The authors thus expect future scientific studies to take developing efficient unstructured data analytical algorithms and applications as primary technological developments. The authors thus expect that future research should take analytical personnel into consideration in the big data analytics framework. In conclusion, the cases demonstrate that big data analytics could be an effective IT artifact to potentially create IT capabilities and business benefits. Through analyzing these cases, the authors sought to understand better how healthcare organizations can leverage big data analytics as a means to create business value for health care.
Q3. What is the common programming model in big data analytics?
Mapreduce is the most commonly used programming model in big data analytics which provides the ability to process large volumes of data in batch form costeffectively, as well as allowing the analysis of both unstructured and structured data in a massively parallel processing (MPP) environment.
Q4. What is the common model for the storage of big data?
A typical model for the storage of big data is clustered network-attached storage (NAS), which is a costly distributed file system for SMEs.
Q5. What is the main trend in the healthcare industry?
The main trend in the healthcare industry is a shift in data type from structure-based to semi-structured based (e.g., home monitoring, telehealth, sensorbased wireless devices) and unstructured data (e.g., transcribed notes, images, and video).
Q6. What was the history of big data analytics?
Big data analytics computing pioneer industries such as banks and e-commerce were beginning to have an impact on improving business processes and workforce effectiveness, reducing enterprise costs and attracting new customers.
Q7. What was the evolution of big data?
Big datawas first defined in terms of its volume, velocity, and variety (3Vs), after which it became possible to develop more sophisticated software to fulfill the needs of handling information explosion accordingly.
Q8. What are the key steps to implementing big data analytics?
According to a recent survey by the American Management Association (2013), mentoring, cross-functional team-based training and self-study are beneficial training approaches to help employees develop the big data analytical skills they will need.
Q9. What is the key to utilizing the outputs from big data analytics effectively?
The key to utilize the outputs from big data analytics effectively is to equip managers andemployees with relevant professional competencies, such as critical thinking and the skills of making an appropriate interpretation of the results.
Q10. What are the main trends in the healthcare industry?
Theincreasing use of sensors and remote monitors are key factors supporting the rise of home healthcare services, meaning that the amount of data being generated from sensors will continue to grow significantly.
Q11. What is the role of analytical personnel in big data analytics?
analytical personnel who have an analytic mindset play a critical role in helping drive business value from big data analytics (Davenport, Harris, & Morison, 2010).
Q12. What is the definition of in-database analytics?
In-database analytics refers to a data mining approach built on an analytic platform that allows data to be processed within the data warehouse.
Q13. How many IT experts participated in the evaluation process?
The authors invited four IT experts (two practitioners and two academics) to participate in a five-round evaluation process which included brainstorming and discussions.
Q14. What are the five generic categories of big data analytics capabilities?
the five generic categories of big data analytics capabilities the authors identified from 136statements in their review of the cases are analytical capability for patterns of care (coded as part of 43 statements), unstructured data analytical capability (32), decision support capability (23), predictive capability (21), and traceability (17).
Q15. What is the prerequisite for implementing big data analytics successfully?
Developing an information sharing cultureA prerequisite for implementing big data analytics successfully is that the target healthcareorganizations foster information sharing culture.
Q16. What is the recent trend of big data analytics technology?
Enterprises have increasingly adopted a “big data in the cloud” solution such as software-as-a-service (SaaS) that offers an attractive alternative with lower cost.
Q17. What is the main trend of big data analytics in the healthcare industry?
According to the Gartner’s 2013 IT trend prediction, taking advantage of cloud computing services for big data analytics systems that support a real-time analytic capability and cost-effective storage will become a preferred IT solution by 2016.
Q18. What is the common use of the analytics layer in healthcare organizations?
this analytic component in healthcare organizations is useful for supporting preventative healthcare practice and improving pharmaceutical management.
Q19. What is the main reason why cases are hard to find?
One challenge in the health care industry is that its IT adoption usually lags behind other industries, which is one of the main reasons that cases are hard to find.
Q20. What is the definition of big data analytics capability?
In general, big data analytics capability refers to the ability to manage a huge volume ofdisparate data to allow users to implement data analysis and reaction (Hurwitz, Nugent, Hapler, & Kaufman, 2013).
Q21. What are the benefits of analyzing unstructured data capability?
According to a 2011 investigation by the TDWI research (Russom, 2011), the benefits of analyzing unstructured data capability are illustrated by the successful implementation of targeted marketing, providingrevenue-generating insights and building customer segmentation.
Q22. What is the definition of big data analytics capability in the context of health care?
with a view of ILM, the authors define big data analytics capability in the context of health care as-the ability to acquire, store, process and analyze large amount of health data in variousforms, and deliver meaningful information to users that allows them to discover business values and insights in a timely fashion.
Q23. How many statements were obtained from the data?
Subsequently,a total of 136 statements directly related to the IT capabilities and 179 statements related to the potential benefits were obtained and recorded in a Microsoft Excel spreadsheet.