Big data is defined as a data group that is so large that it causes problems of searching, collection, storage, analysis, and sharing of the data. Big data has four main characteristics. They are; volume, variety, velocity, and veracity. First, volume is the amount of data that is to be analyzed. Variety is the structure that the data in question has. Velocity is the amount of time taken to process the data from the time it is collected to the time it is being streamed. Veracity is the amount of quality of the data that is being analyzed, finding out whether it is viable for use or not.
These characteristics are relatable to health in different ways in which these factors influence big data. The world is producing more and more data as time goes by. Millions and millions of Exabyte of data are produced daily. Analysts say that this amount will only go higher. Ironically, as much as the data amounts increase, only a small fraction of this data is structured. Just a small amount of the data created daily is structured. The amount of unstructured data is over fifteen times the amount of structured data. Unstructured data includes personal texts, video and audio messages, manually written notes, and many others. Over the next several years, more gadgets that are personal will be introduced into the market. This means that the amount of unstructured data will only increase. In health care, data volumes increase when health centers try to structure the unstructured data that they have. Many healthcare practices are investing into online methods of data structuring like Cisco and the Oracle Company.
Weather forecasting facilities have an enormous amount of data. The data that is generated in weather stations and other weather forecasting facilities are structured, unstructured, and semi structured. In a department like weather forecasting, enormous amounts of data are collected every day from the monitoring of every day’s weather patterns. Structured data is the digital information that can be easily stored to be worked on or just retrieved later. With the technological advancements that have been made over time, weather-monitoring equipment are fitted with computer programs that make it easy to collect random data and relay it to computers in a way that is easy to manipulate and retrieve in the future.
Velocity is the concept of determining the speed in which the data is converted from unstructured form to when it can be streamed. Satellites and other weather forecasting equipment are in constant patrol monitoring weather patterns. This means that the amount of data that is being relayed back to the computers in weather station is constantly changing. It is therefore advantageous than even traditional ways of collecting weather information. This makes it easy to convert into more structured data and streaming to the relevant channels for streaming. The amount of data collecting equipment in weather forecasting stations will only increase as time goes by. More accurate machines that predict the weather more accurately will come in the near future. It is therefore important for the weather forecasting stations to invest in efficient machinery, which will structure the data faster. This is also necessitated by the changes being observed in weather and climatic conditions. There needs to be less variety in the weather forecasting industry so that more data is structured and the data that is semi structured and unstructured is converted as fast as possible.
The veracity of the collected data is also an important part in the big data that is processed daily. The video shows the history of climatic patterns of the earth for the last ten years in less than three minutes. The quality of the data that is processed is important because it will be used to predict future weather patterns. The quality of the data that is being process reflects the quality of the data that will be relayed to the public. This information is important since it helps scientist figure out whether or not there will be famine, the occurrence of tsunamis or floods that may endanger human life. It is therefore important that the data is reliable. Weather stations must look into means of making their data more reliable. There are such companies in the market today. Cisco and IBM are companies that can be tasked with verifying the quality of data that should be structured before it is streamed.
In the second video Deborah Estrin explains how small data can be used to figure out the health changes that a person is going through at a particular time. She explains that an average person constantly leaves a digital breadcrumb trail as he or she goes on with their daily life. She suggests that the equipment that is used in day-to-day activities could be used to get health information about us and store this information in a cloud storage application. This information could be later retrieved in form an image of our health status.
She explains that the advantage of using small data to make changes in our health is that small data is easy to analyze to come up with an informed conclusion.
Estrin, Deborah. "Deborah Estrin: Small data can show big health changes." YouTube. Version 67. YouTube, 29 May 2013. Web. 20 Feb. 2014. <http://www.youtube.com/watch?v=lAEhSGYEHWU>.
Feldman, bonnie. "Big data in Health Care." Big data in Health Care. Version 23. N.p., n.d. Web. 20 Feb. 2014. <http://www.west-info.eu/files/big-data-in-healthcare.pdf>.