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On other PS2 EmulatorsDo You Trust Big Data? by Steve Garrick In a recent New York Times article, Google Vice-President Eric Schmidt commented, "Nothing will have a greater impact on the quality of our lives and on the very survival of our species than the ability to deal with and manage our information overload." This is the latest in a string of pronouncements about Big Data. "Big Data" is the use of large amounts of information to make decisions based upon current trends and accurate data. If you are considering using data analytics for your business, this "Big Data" explanation is not going to be helpful to you. Unless you have significant data already in place from a variety of sources, you will struggle to find comprehensive data you can base decisions on. Successful "data analytics" requires, not just traditional data, but current and accurate information from current trends. When we talk about data analytics, we are talking about organizations with a critical mass of data, and the ability to see trends, analyze data and make decisions based upon current trends. The types of organizations using data analytics are numerous and included are industries as diverse as retail, finance, manufacturing, healthcare, or marketing. The first companies to implement "Big Data" were companies in the financial sector. Financial companies will continue to be leaders in the use of "Big Data" for analytics, and should continue to benefit from the implementation of these new technologies. Using data analytics to determine the future value of a company is important to ensure a robust and competitive organization. Healthcare will benefit from the use of "Big Data" for analytics. While the explosive growth of healthcare data has created "Big Data," as described by McKinsey & Company, the need for a common language, standardization, standard tools, and a culture of sharing will be the key success factors. Healthcare organizations today are overwhelmed with data. For the healthcare industry, Big Data is not the easy fix it was assumed to be. Regardless of the industry or the type of organization, successful data analytics requires organizations to have a clear vision for the future and a long-term focus on what the organization really needs to know. They will also need to acquire the right data, from the right sources, to be able to make the most accurate and timely decisions. As with all new technologies, organizations need to consider how to work with existing processes and systems to facilitate the new process and result. On the path to
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