Big Data is Better Data

Big data will indeed improve our lives, but there are still problems that we need to be conscious of.

The term big data does not solely refer to large data sets, but more importantly it is more focused on the frameworks, techniques, and tools used to analyze it. In general, it is a collection of data sets that are very large which can vary in sources and form. This data can be gathered through any data generating process such as search engines, social media, and public utility infrastructure; however, this information could be either structured, semi structured, or unstructured. There are amazing benefits to real time big data analytics when it comes to detecting errors, advantages from a competitive standpoint, improving profits, and providing better healthcare. Nevertheless, as valuable as big data can be, it brings us serious challenges, such as utilizing it to our needs, invasion of privacy, and other negative affects from abusing its power. Big data will indeed improve our lives in many ways, but there are certain guide lines that we must follow and respect when using it for making the world a better place.

The principles of engineering and IT can be used to process and store this data as well as further automate the collection of more data. It is important to know that the primary value from big data is not from its raw form, but is instead from the processing and analysis of it which brings us the insights, products, and services that it gives us. Big data affects organizations across practically every industry including banking, education, government, health care, and retail. What we need to be focusing on is using this data and analyzing it to improve society and innovation, just like how it did in the past. It is at this point of history that there are larger data sets than ever before, and the potential applications this data can provide us is limitless.

Every business needs to use big data in order to grow and succeed as a company, regardless if they are a fortune 500 company or small businesses. Disregarding what field a business operates in or the size of it; as data collection, analysis, and interpretation become more easily accessible, data will become an asset to every business. Big data will enable companies to collect better market and customer intelligence. This helps companies improve profits and defeat competition by letting us know what customers want, what they will use, what channels they use to buy, and so much more. Businesses must use their data as an asset to improve by identifying trends, finding their competitors, and improving operations.

Big data applies to us as a modern oracle for business and other organizations, just as the Oracle of Delphi directed the ancient Greeks. However, businesses that completely depend on big data can make bad decisions and miss crucial opportunities. The problem is that these companies have fallen prey to quantification bias, the senseless preference for the measurable over the immeasurable. Focusing entirely on numerical data works when analyzing finite systems, but understanding progress requires thick data: the qualitative research that comes from human feelings and interactions. One strong believer of this powerful ideology is Tricia Wang, who is a global tech ethnographer that studies how technology and humans shape each other. Wang recommends that many businesses have invested massively in big data, convinced that its findings will save them money, provide solutions, and grow their profits.

When Wang was a researcher for Nokia in 2009, she operated field studies in China to find out low income families use technology. Her qualitative research confirmed many poor Chinese families strongly desired smartphones, and some would invest their monthly income to own a replicated iPhone. Nokia ignored these insights because they only contradicted its big data and as a result, Nokia failed as a business as touch screens were the new trend. It is dangerous for companies to reply on quantification bias as it is easy to disregard important findings that are not comprehended numerically.

What we must focus on is integrating big data and thick data, as Wang suggests. For example, Netflix’s recommendation algorithm allowed them to make metamorphic improvements and improve profits. Netflix used data analytics to find out what it is that their customers want most and how they could use this as a valuable opportunity. This thick data revealed that viewer’s weakness to binge watch; the information that Netflix used for their advantage for success. Improving algorithms with thick data can improve many aspects of society when it comes to business, law enforcement, health, and saving lives. This is one example on how big data should be used, so that businesses can benefit from it and not pursue the wrong path.

When explaining and understanding how big data is helping to make the world a better place, there is no better case than the applications being found for it in healthcare. Over the last few years, we have seen immense advances in the amount of data we consistently generate and gather in just about everything we do, as well as using technology to analyze this to our better understanding. The crossing of these trends is no other than big data, and it is absolutely known to help businesses become efficient and productive; in this case, healthcare is no different. Even more than bettering profits and cutting down on wasted time, in health care big data is being used to detect errors, epidemics, cure disease, improve many lives, and of course saving peoples lives. As the worlds population is growing larger, we are finding ways to improve and extend human life. Treatment and cures are rapidly developing and the reason for this cause is greatly influenced by big data.

Health care serves to a variety of people and contributes to a significant part of any country’s economy. When it comes down to providing care to those who are in need, this is originally initiated by analyzing multiple causes, whether it be claims or someone’s information to health risk assessments. One instance of this is health risk assessment data, which can provide an image of possible plan management among new members. Without all of this data, health plans would have to delay this process and would not be able to detect who requires care coordination. Furthermore, healthcare analytics can influence he different types of health care plans to process what provokes people and how to change behavior. Focusing more at screening rates among people in different demographic groups can greatly assist the identification of barriers to screening by determining the best way to complete these urged screenings. When trying to provide to such a large population, it is even more crucial to gather information as a way to improve health care and to lower its cost.

As more information and data on health care and disease patterns are being developed, there will be more useful insights which will benefit new programs in health care to be more quickly and better adjusted. Studies of health care management and wellness programs have had a huge impact, for instance a recent study tested the hypothesis that the liability to a targeted care management program can differ the possibility of having appropriate medication dispensed, increase medication adherence, and opportune clinical tests performed. The information founded in this study shows that about 9 percent of fewer members would have had a prescription for asthma controller medication without the presence of the program. Now this same study then considered to look at pneumococcal vaccination and statin medication metrics, the results showed that in the fourth year, without the care management intervention, almost 20 percent of less members would have had a prescription for statin medication.

Improved health care analytics brings us more improved programs and the power to create new ones. The potentials of improved outcomes and fixed costs from analyzing the big data are extensive. It has been recommended that preventative actions such as early cholesterol screening for patients with associated histories and hypertension screening for adults, will reduce the total cost of healthcare by over $30 billion. Though big data had already had a great impact on wellness, we must continue use it as data is as a tool to make this happen so that we can even further improve healthcare for everyone.

Big data produces a more comprehensive picture than small data, leading to more accurate conclusions and the world will be unable to solve its most complicated global issues without confidence on big data. The recent conception of machine learning, through which computers collect data and teach themselves, has increased the value of big data. Although big data and machine learning have excessive potential for good, they also have a sinister side. Big data holds immersive power, and society must employ it responsibly. Machine learning, which is a development of artificial intelligence in which computers gather data and teach themselves, has increased the value of big data. In todays world, machine learning is at the heart of many technologies, including self-driving cars, search engines, and voice recognition systems, just to name a few. Through machine learning innovation, a specialized computer was able to identify unknown indicators of cancer in breast tissue biopsies.

Though big data has the ability to improve human life, work, public health, universal happiness, and more, we must remember that big data also has a great threat. One scenario predicts a future where predictive policing could employ data and mark to hold people accountable for crimes that have not occurred yet. More importantly, big data can and will change the employment landscape and transform or eliminate many white collar jobs, just like how it did for blue collar jobs. Society must treat big data responsibly and use it to meet human needs. Big data must become a tool to help humanity understand the world and our place in it.

Big data will indeed improve our lives, but there are still problems that we need to be conscious of. As moving into the future, the challenges include protecting free will, human determination, and integrating business tactics. It should be well aware that we must be careful, and take big data so that we can adjust it for our very human needs. We must learn how to better control this technology and not abuse it. Big data is going to help us understand our lives, our work, and decision making. It is going to help us manage our careers and direct lives that include satisfaction, innovation, contentment, and better health.

Bibliographic References

Chen, M. (n.d.). Big Data: A Survey. Retrieved September 30, 2017, from https://link-springer- com.proxygw.wrlc.org/article/10.1007%2Fs11036–013–0489–0

Pan, W. (n.d.). Big Data. Retrieved September 30, 2017, from

http://ieeexplore.ieee.org.proxygw.wrlc.org/document/7887650/

Wang, T. (n.d.). The human insights missing from big data. Retrieved September 15, 2017, from

https://www.ted.com/talks/tricia_wang_the_human_insights_missing_from_big_data

What is Big Data and why it matters. (n.d.). Retrieved September 02, 2017, from

https://www.sas.com/en_us/insights/big-data/what-is-big-data.html

Cukier, K. (n.d.). Big data is better data. Retrieved October 08, 2017, from

https://www.ted.com/talks/kenneth_cukier_big_data_is_better_data