The Importance Of Data Trends In Big Data

These extremely large data sets may be analyzed computationally to reveal patterns, trends, and associations relating to human behavior and interaction. These analysesaffect us on day to day basis positively and negatively and the legality of how this information is collected and the laws that apply may be unclear. Both with or without users' knowledge, consumer personal data is collected from every daily, digital activity; from purchases, web searches, amazon searches, browsing history, and phone use. This data is generated, and then downloaded and stored. [15] Companies can then use this data to create "data sets" or large files of users' data to produce customer profiling. This data can also be used by police, the governmental bodies, scientists, businesses, military, and other industries where occasional breaches of data are expected .[16] Breaches and leaks of personal information including phone calls, credit card information, home address, and personal phone numbers are examples of information that is logged and stored by these corporations while making "data sets". Much of this information is being processed and sold to marketers for the purpose of marketing their products. This information is stored digitally and in some cases, regardless of the security of the information being stored, there are risks of unauthorized parties

The continuous stream of data can be turned into valuable, actionable information practice leaders can use to enhance data security and enforce compliance, improve financial health and limit liability exposure.

It’s a value care for U.S patient population. Back to the digital health care prediction, Dr. Brown indicated that the vast amount of untapped data could have a great impact on health that exists outside of medical systems. However, there were challenges when it came to collecting healthcare data. First, the unstructured big data which presents in medical literature. How do we know which one to read? Second, a data associated with a single patient in an electronic medical record (EMR). An electronic medical record came with a structured data and an unstructured data. There was a question about the HIPPA regulation, and Dr. Brown assured that IBM adhered to the regulation completely. All these pooled data were placed in the Watson Cloud that aggregated the data together to perform different analytics. It’s all automated system. Then, IBM acquired Truvan that tracked insurance and reimbursement data and enabled to see overall

The first evidence-based intervention used is that of scheduling software. Utilizing technology that collects registration data and analyzes it is imperative in reducing patient wait times. Healthcare facilities can utilize predictive data to forecast

The need for analysis, collection and management of human resources information has outpaced the development of human resources information systems in many health care organizations.

For Payers - Since heath data can be made available to consume and analyze, organizations can take advantage and reduce their existing costs related to patient care. Adoption of digital heath data is estimated to save about $77 billion per year for both inpatient and outpatient care[5]. Better decisions can be made by Payers by taking the benefit of intelligent Algorithms which predict disease possibilities and provide more insights on target audience to better understand the entire healthcare system.

Through the Big Data film, viewers are taught that data tracked through search engines can be instrumental. The tracked data can be used to predict trends over time. For example in the film, the researchers were able to track the number of times that flu symptoms were searched. Then with this information, the researchers were able to accurately predict the onset of a flu season prior to the Center for Disease Control report. Additionally, this data can also be used to keep the information up to date. For example, during the hurricane season, people used Twitter to provide updates on where the damage occurred and give details on to what degree property was damaged. Recently, the city of Tallahassee used twitter to give updates on power outages that occurred during the most recent storm. On Twitter, the city of Tallahassee released the areas affected by the storm and approximated guess of how many people were without power. Data can be useful because it helps to keep people informed and permits further analysis of everyday tasks performed on the

Study and analysis of the health care systems have become a necessity to improve its performance over time as it must meet a number of often conflicting objectives such as providing better and more efficient patient care while minimizing the cost of health care and resources (1, 2). Hospital management as an important component of healthcare systems may face with numerous challenging tasks while achieving these goals (2-4). In a hospital system, the flow of patients is a determinant factor that affects the performance of healthcare delivery processes. The decision problems of a hospital are directly related to and affected by the month to month changes in patient flows. The short-term forecasting of patient flows is the fundamental input of short-term decision making and planning on hospital and laboratory equipment, staff resources, food and laundry service demands, and like it. Furthermore, the long-term forecasts of patient flows are vital to long-term planning decisions about resources and capital budgeting which it’s positive gains, in the long run, will lead to a sequence of capital expenditure (5). In this context, the knowledge gained from an accurate prediction of patient flows would provide valuable information for resource allocation and strategic planning and also has the potential to minimize patient care delays,

Health Data Management help their subscribers focus on the most important issues and topics in the news such as revenue cycle analytics and accountable-care models, electronic health record platforms and data storage, telemedicine and mobile applications.

The human resources information systems (HRIS) have evolved much like the electronic medical record movement. “It has the capability to maintain employment records of all staff members, and employers can use it to collect metrics surrounding the firm’s staffing, performance management, compensation and benefits activities” (Henderson, 2014). Much like an electronic medical record, employee demographics are similarly entered and retained. Wage information, employee licensure, and trainings could be stored similar to lab results and employee health records could be viewed as exams. Human resources information systems and

The world of healthcare is going through a transformation in the IT world. The capture of “Big Data” has only begun. Applications are being introduced that help individuals make sense of this raw data, which is proving to be very beneficial in the healthcare world. Although in its infancy, the advancements we see in this research paves the way for a very promising future in healthcare. The use of Big Data proves to show how raw data can be turned into very useful knowledge and therefore improve health-related outcomes as well as control costs. The opportunities associated with “Big Data” are only being accelerated and the use of this data will serve as a catalyst for increasing patient knowledge.

I am writing this memo to make you aware of a significant trend of companies using big data an-alytics to attract talents and improve human resource (HR) strategies. As more companies begins to utilize their data resources to access and retain their talent pool, this will potentially affect your company’s current and potential profitability in the upcoming years. After performing industry, company, and trend research, I recommend that you should acquire Wanted Technologies and incorporated their data analytic tools to help create innovative HR strategies for your clients. With your previous experience of Arthur Anderson’s partial acquisition, I believe you will be able to execute this proposal in the most efficient way to remain as a

“users don’t fully understand the scope of the data that is being collected on them — or how small amounts of data can be used to create a much more detailed portrait when matched with information from third-party sites that collect and share various types of customer information with each other” (Smith 2014).

The amount of data created by people every year has gone up significantly in the past few years. In 2015, there was 7.9 zettabytes of data created worldwide, and that amount is expected to grow to 35 zettabytes by 2020 (Lee, 2016). The increased popularity of smartphones, tablets, and other connected devices in recent years have contributed to the growing amount of data being created. Businesses see this data as a way to improve their fortunes and are coming up with ways to profit from this data. To obtain the data in order to utilize it, businesses collect or purchased data that consumers create on the internet. Critics of this collection of data believe that these businesses collecting the data are acting unethical for invading the privacy of consumers (Lavandera & Morris, 2012). However, considering all the relevant laws, guidelines, and the impact on society as a whole in a deontology and utilitarian viewpoint, the collection of data for commercial use is ethical.

The rise of big data analytics has affected the 21st century American economy and businesses in many positive ways. One area where it is lagging, however, is the healthcare industry. For years, America has paid more for healthcare than any other country on Earth. This can be attributed to a number of reasons, but a large factor among these is the inefficiency of the current healthcare system and its failure to adapt to cost-saving analytics like other industries have. That is where big data analytics can step in and serve a great purpose. Big data is the process of taking mass amount of information across different, but interrelated areas in order to derive deeper meanings, insights, trends, and analysis through the usage of high-speed, high-capacity algorithms. This can be huge when one considers that as of 2014, there are 44 petabytes of information on patients in the electronic health records system. (Raghupathi) This can include medical history, imagery from patient scans, lab results, and a vast array of other information. Couple this information with the push to integrate individual’s social media posts, personal DNA sequencing, and vital data collected by smartphones and wearables, just to name a few, and it becomes evident that we as a species will be generating exuberant amounts of medical data. There are some people, however, who feel that having this information integrated into any kind of database poses a risk to the privacy of their most personal,