The Future of Big Data

            Big data includes the data settings that are large in volume or compound bin nature that the ancient data processing cannot be used.  Almost everyone in the healthcare family will agree with the fact that data can drive not only marketing and sales but also identify its outcomes as well. With that, big data and using it are two diverse approaches.  Those who review its outcomes always determine not only the future of an organization but also the end results of the patient care (Anderson, Janna & Rainie, 32). 

            In many companies, big data is used to categorize the customer’s needs.  Marketing in such companies remain separate from the rest of the enterprise and may be operating without profits of the available data to promote products.  While the type of data used to modify the end user experience and to eradicate the one size fits all solutions that given today, customers still experience approaches by vendors that only minimally change solutions to them, while the client and consumer patience is the main thing.  The information needed to address the specific requirements of the customer is becoming more available but getting into the right track remains a confront (Anderson, Janna & Rainie, 38). 

            In healthcare, big data remains more unproven although it has not stopped companies and marketers from jumping on the big data bandwagon.  Big data can provide a better care quality and less expenditures but the proof to support these claims to date is uncertain at best.  Big data analytics take masses of data from many diverse sources to discover patterns that can be useful in solving problems.  These sources include clinical, financial and operational data and often work in the cloud as well.  Most of this data is made to allow patient connection by taking a proactive and a conservative approach.  Clinical data validates from across the range of care to often include not only lab results and unstructured data (Sander, 92). 

            Big data has started to disrupt the ancient databases and data warehouses that will be the next big wave of advancement in data management.  Innovation has to be faster or cheaper to overcome the inactivity of an ancient approach in Information Technology.  Apache made at least ten times less expensive to house data by distributing it across commodity hardware and opening up new software. There are some edges and hidden costs, but this was compelling enough to get significant market grip versus legacy hard work and software.  The main utility of the Hadoop distributions has morphed towards used mostly by a storage layer with a system of other tools buildings analytics value above it (Sander, 95). 

            This is because the next challenge has been in processing the data for understanding.  Map reduces turns to be a bit complex for many to influence in building analytics applications both that use unfamiliar language and limiting in its flexibility. The Apache spark is swiftly becoming the main aim of the analytic engine for Hadoop storage offering enough time and graph liability. The next problem of the machine data is that as the data volumes have become more expensive to handle while its meaning has become harder at its scale. The important news is that machine learning works better to the data that is thrown on it. The math machine learning is new and its economics has changed (Sander, 102). 

            One of the most interesting areas that the big data is used is the pediatric cardiology and this is where analytics are used to make patients more specific proposals for treatment. The Pediatric Cardiac Critical care uses big data to try and improves the quality of care by collecting data to the critical practice and outcomes from each patient’s medical record and analyzing the data so that they can provide clinicians with timely presentation criticism. This predicts the culture of ongoing improvement through analytics and mutual learning. This disease is registry is also important as we move towards a future based healthcare system (Dumbill et al, 45). 

            Big data in radiology is more about decision support than anything else and plays an important role in expressing the way radiologists  said that they always use the clinical policy to support the computer-based diagnosis. The idea is not there because the world, while seemingly large, it needs to be inspired in the confidence level needed by radiologists.  These large data sets can be used in the future clinical decisions support systems such as CAD to study patients with the same features and calculate the likelihoods of malignancies and other diseases.  Putting this in future forecast, data mining needs some more coding and tagging which will make the data easier in organizing and searching through. This will promote both radiology identify and finally the patient outcomes through improved diagnostic capability which are made possible through using the big data (Dumbill, 66). 

            Looking at the application of the World Graph of the government, the aim of any current government is to protect the rights of its citizens, sustain and conserve markets and to maintain the education systems that make the society to advance.  The future data that is already gathered about people shows a compelling story about what they consider good and bad or what they need for the future.  Pairing data from anyone with the analysis and the ability to route resources to people who can solve societal predicaments can be more effective than the current systems (Dumbill, 78). 

            Based on education, it is important that teachers teach students in physical buildings.  It is rather important for the students and families to pay lot money in college education.  Algorithms can parse classroom discussion boards and forecast the students’ grades and scores with a high degree of correctness.   If computers know of every nuance of a person, their grades can be computed. The current data movement to the online movement is a small step towards the future (Viktor, 32). 

            In addition to this, mechanical teachers can review your knowledge level and the costs of education that may be more seen to more students.  The universal data and advantages give information about a person to help them make life big with greater decisions. This data analyzes information about a student to review what career path he is best suited. Professional works that need data engagement can be done more effectively by the Universal graph used by a human.  This does not mean that people will not have meaningful careers.  The universal graph will check the field that is more suited by your abilities.  Humans can reach a new degree organization based on the future of the big data of the universal graph (Viktor, 45). 

            Widening the scope of the Company, the universal graph can help review what the new products or services it should offer.  Employees should be valve for the management and this should lead to more training and support to help them succeed.  Based on the country level, the universal graph can help guide the nation’s plans of the geopolitical issues and from effective programs that would solve the impossible problems such as poverty and social inequality.  Looking on the future of the big data, the universal graph can help people fix many of the global social ills so structures such as the government of the judiciary system that could be formed together (Dumbill et al, 87).    

            Social media sites such as the facebook and twitter can learn about your personality using the current data system.  It does this through parsing the vacation and the photos that one posts along with the new articles you link to and the thoughts on any issue.  For instance, Amazon builds a sense of who you are based on what you buy.  The future data in all these systems shows the prospect of the universal graph.  In future, the universal graph will help one reduce the trial and errors so that people can find a life partner, for instance, choosing a better college or university to go (Michael &Telang, 93).   

            The future data is determined in the universal graph so that one can better understand and make future actions.  Graph technology is currently helping the moving data of the large companies such as Netflix that has improved connections.  The graph technology will help the utility companies to forecast when they will have peak periods in either the usage or the company equipment failures.  The banks will also be able to predict more instances of theft and interior trading (Michael &Telang, 119).  

            The future of the big data has not come yet, but its prospect is convincing.  The current graph technique will help companies and organizations learn more smoothly.  It future is prospected to help people reach their potential and live more fulfilling lives (Michael &Telang, 123)

Conclusion

            The big data will adjust business and businesses will change the society.  The world that is based on the big data is still very new and as a society, people are not good at handling all the data that can be presently corrected.  Technology will endure surprising us and what is more certain is that it will be different. 

 

Work cited

Anderson, Janna Q, and Harrison Rainie. The Future of Big Data. Washington, D.C: Pew Internet & American Life Project, 2012. Internet resource.

Dumbill, Edd, Alistair Croll, Julie Steele, Michael K. Loukides, and Mac Slocum. Planning for Big Data. , 2012. Internet resource.

Klous, Sander. We Are Big Data: The Future of Our Information Society. Place of publication not identified: World Scientific, 2016. Print.

Mayer-Schönberger, Viktor. Learning with Big Data: The Future of Education. , 2014. Internet resource.

Smith, Michael D, and Rahul Telang. Streaming, Sharing, Stealing: Big Data and the Future of Entertainment. , 2016. Print.