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Internet of Things is evolving. Effective IoT requires software modifications, network communication support changes, platform shifts. The missing key is the data infrastructure to support IoT. Big data analytics is an advantage in today’s world, but it is essential for the coming IoT revolution. Big data can help IoT initiatives in many ways. To know more, follow: http://it.toolbox.com/blogs/itmanagement/five-ways-big-data-can-improve-your-iot-initiative-69958
Big data - which admittedly means many things to many people - is no longer confined to the realm of technology. Today, it is important in any business. In addition to providing solutions to insurance companies' long-standing business challenges, big data solutions offer the power to transform processes, organizations and entire industries. Big data is especially promising and differentiating for insurance companies. With no physical products to manufacture, data is arguably one of their most important assets. Financial, actuarial, claims, risk, consumer, producer/wholesaler and many other types of data form the basis for every decision an insurer makes.
Insurance companies will realize value by effectively managing and analyzing the rapidly increasing volume, velocity and variety of new and existing data. By putting the right skills and tools in place to better understand their operations, customers and new markets, insurance organizations will be on the right track to compete and thrive in this global, dynamic marketplace.
A U.S. regional bank while reducing its staff and technology cost wanted to see how it could maintain its collection rate. A consultancy based in Chicago and Bangalore analyzed the actions of a U.S. regional bank such as calls, mailers and IVRs and concluded that the bank was overspending. The bank was thus able to reduce costs by a million $. Analytical companies are now investing in platforms and products to fill the void in analytic stack. To know more:
Continuously evolving technology in the healthcare sector is creating immense pressure on the healthcare providing concerns, to meet their highly demanding service quality and financial goals. Organizations are trying to develop step by step connections, by keeping track of all the different stages a patient has to go through, once he enters into the concerned healthcare system. The healthcare industry has been giving a lot of effort in the development of the health information system and big data analytics, in order to improve the healthcare service. As, more and more stages of the healthcare cycle becomes electronically recordable, the easier it becomes to keep track of the patients and their health situations. Read more at: http://healthitanalytics.com/news/health-data-interoperability-requires-patience-persistence
As the typical scenario in any data analysis includes more than one type of data source, working with large datasets, messy and unorganized data, there is a huge need of data prep required. Most data sets are relatively dirty and need to be thoroughly cleaned for the analytic result to be usable. The need to have some structure for reporting and analytical tools to grab onto resulted in a boom of data prep.
It is very imp to have the data validated in the initial stage, because if that goes wrong, then everything downstream of that becomes very problematic. Thus we need to have the data ready for analysis and to avoid any non-value add, which is achievable by big data prep.
The introduction of Hadoop has changed the outlook of businesses. It is a software system that has made processing large sets of data located on distributed servers an easy task. Hadoop is mainly used for analytical purposes boosting business performances and customer relationship management. It has worked wonders for small businesses as it has incorporated concepts of big data analytics. Data is much more accessible now and the cost of procurement has been drastically reduced. Some convenient features in Hadoop has made it much more attractive for small businesses. Hadoop has made effective use of big data possible to optimize businesses. With its value increasing day by day, more and more companies from various sectors are going in for Hadoop. Read more at: http://www.dataversity.net/an-introduction-to-hadoop-for-small-businesses/
According to a survey, big data analytics and informatics skills are the ‘prospective’ two most important resources, to be used by the healthcare providers in their decision making and data management processes. The health information sector is experiencing some major changes, like, for example, the conversion of paper health records into electronic health records (EHR). Health Information Management (HIM) is also evolving, to be utilizing big data in population health management, predictive analytics, clinical quality enhancements, etc. Health Information Management, needs to view data as an asset, in order to utilize the data, in the best possible way. Read more at: http://healthitanalytics.com/news/him-healthcare-big-data-analytics-skills-increase-in-demand
A certain cross-country survey revealed that the Internet of Things (IoT) was first adopted by the Healthcare Industry. Organizations that adopted the IoT, believed that they could meet business challenges like patient engagement, loyalty, safety and satisfaction without any delay. According to Laura DiDio, Director of IoT Strategies Enterprise, the need for IoT is felt highly by enterprises to address and solve pragmatic business issues. Andrew Brown, SA’s Executive Director of IoT and Mobility says that IoT can also be used for cost savings, development of new services, increased competitiveness and better understanding of the business. It can be said that the Internet of Things has great potential in the field of healthcare and with evolvement of mobile capabilities its growth rate will be escalated. Read more at: http://healthitanalytics.com/news/healthcare-industry-is-an-early-internet-of-things-adopter
Big data analytics in healthcare industry, encompasses the whole transformation of data, beginning from the recording of the fundamental data to predicting diseases and alerting patients. Any health concern’s big data analytics capabilities fall into three major categories, descriptive, predictive and prescriptive. Descriptive analytics quantifies past events, like for example, the number of patients, who visited the hospital in the last month. It provides considerable insights into the data which can be later used to make predictions, regarding disease trends. Predictive analytics uses these descriptive data to predict the future, which often reduces unnecessary costs, related to controllable diseases, by making early detections. Finally prescriptive analytics provides suggestions on ways to mitigate the imminent threats, suggested by predictive analytics. Hence, an efficiently functioning data analytics infrastructure, incorporates all the three processes and is invaluable in the healthcare industry. Read more at:
Sigmaway consultants have worked with clients in benefits solutions workspace providing analytics on healthcare plans. For more details visit http://www.sigmaway.us/
Digital privacy is dangling on the edge of the cliff as public cynicism has always been high. To battle this, there has been innovation in Big Data: Customer Empowerment. Usage-based insurance (UBI) programs can allow people to trade in their personal data in a transparent market transaction. Companies thus have data owners that are treated based on their data, thereby increase brand satisfaction and reaping larger profits. A survey hinted that half the consumers in U.S., U.K. and Australia are alright to share personal data in exchange for product/service incentives. Drivers of automobiles can now track their driving behavior with sensors that calculate personal driving profiles that are then factored into their auto insurance. Read more at: http://techcrunch.com/2015/06/29/the-latest-big-data-innovation-is-consumer-empowerment/
When it comes to the healthcare industry and its ongoing revolution, Big Data and Internet of Things have become an integral part of it. As more and more health data is now being digitally stored, the seer amount collected on patients is growing at exponential rates. Big data, already used for the mapping of the human genome, is now showing its value in the analysis of large complex data and thereafter in predictive analytics to find people most at risk of a certain illness. Predictive analytics isn't the only place where Big Data and IoT have helped in the advancement of healthcare services. There is now the possibility of analysis of data generated by IoT devices to help calculate medication tailored for each patient and also calculate their results in advance. Read more at: http://www.predictiveanalyticsworld.com/patimes/the-iot-and-big-data-are-teaming-up-to-push-healthcare-further-than-ever-0627156/
By making use of excess of data available and information and communication technologies (ICT), smart cities can now address the various economic, spatial, social and ecological problems. Although data analytics forms the core of business strategies, yet very little is known about new business models within smart cities and urban living. Recent advances in Data Analytics have shown promise than city data analysis and its use can generate value for municipalities, companies and individuals. From relatively simpler analytics techniques to more sophisticated one, the available tools can adopted to obtain the desired results. For example, when the enormous volume of the data poses serious challenge, clustering technique can make the dataset manageable. Read more:- https://icrunchdatanews.com/smart-data-analytics-smart-cities/
Location analysis is a very important part of Big Data classification in automobile segment. Big data analysis is used in every stage of production and marketing of automobile industry. Product Design – Data is collected from customers who would help them to make newer improved models. Supply Chain – With the help of Big data analysis manufacturers can now analyze different suppliers based on various aspects and reach a decision. Marketing – Helps in identification of the right kind of customers. Aftermarket – Helps In improving logistic and sourcing processes. Financing – It enhances the understanding regarding the market of each model. Read more at: http://www.smartdatacollective.com/anandsmartdata/325598/big-data-automobiles-use-cases-today-and-opportunities-future
In today`s business world, time is a precious resource, so there is increasing demand for a faster system of data analysis. An emerging open source analytics tool called spark is slowly gaining popularity and is being used for getting faster results obtained from big data analysis. Earlier many companies used and relied on Hadoop for processing and analyzing information, which used to take days to arrive at a meaningful inference. The spark analytics technology uses a completely different technique for storing data than Hadoop, with spark data is directly written in the memory rather than storing in disks, which increases the speed of data analysis remarkably. There are also other interesting technological features for which spark is gaining attention.To know more read: http://blogs.wsj.com/cio/2015/06/03/spark-a-tool-at-big-datas-cutting-edge-helps-under-armour-perform-faster-analytics/?KEYWORDS=analytics
Responsible for the largest and most complicated science experiment, the LHC, CERN has tried to uncover the secrets of the universe. Its major experiments are all in the domain of Big Data. How? Well the LHC single handed generates 30 Petabytes yearly. They use effective data warehousing and Big Data Analytics tools to make sense of such large amounts of raw data. Crunching all the data collected from the 600 million particle collisions per second requires enormous processing power. Distributed computing gives them access to enough processing power and storage capacity otherwise far too costly to build into one data center. The data can be accessed at greater speed by researchers wherever they are in the world now. Read more at:https://www.linkedin.com/pulse/big-data-uncovering-secrets-our-universe-cern-bernard-marr
The evolution and advancement of modern technology has led to a remarkable development of how business is done. With this rapid progress, the complexities in terms of how these technologies are used, has increased largely. Often the names and terms are clubbed together, and it becomes difficult for non-technical business leaders to understand and identify the independent usage of these technologies. "Big data analytics", "marketing analytics", "social media analytics", "audio stream analytics", etc. are some of them. It seems that analytics are often clubbed with other words, many of which are associated with storage and inflow of large volumes of data. If the volume of the sample is adequate enough to give a statistically valid output, then analytics can be executed without resorting to big data .To know more read: http://www.mytechlogy.com/IT-blogs/7973/does-analytics-need-big-data/#.VXE5WM-qqko
From Software and Platform as a service to data as a service, the trend has always been to evolve to the requirements of the current generation. The next step is mixing them all together and mass upscaling of the data in the system to provide Big Data solutions as a service (or BDaaS). Multiple businesses in the past have sprung up and are offering cloud based Big Data solutions. Big Data refers to the large, mostly unstructured information created and stored, and the analysis and use of this data is called Big Data Analytics. BDaaS is a term used to describe the outsourcing of Big Data functions to the cloud. It includes the supply of data, providing the analytical tools and the actual analysis of the data. BDaaS can also include consulting and advisory services. Read more at : http://www.forbes.com/sites/bernardmarr/2015/04/27/big-data-as-a-service-is-next-big-thing/
With plenty of big data on its hands, the healthcare industry will be able to improve quality and patient outcomes only if it is able to extract meaningful, actionable insights from this bounty of raw information. To reap the benefits of healthcare big data analytics, organizations should bring about cultural and leadership changes to promote analytical approach to the practice of medicine. Research puts it that to achieve improvement, multiple types of data are required which can identify opportunities, measure progress, and help users understand what works. Using predictive analytics to identify high-risk patients, reducing infections and adverse cases through implementing evidence based protocols and realizing the importance of patient-centred care are some of the measures that have been reported to have made an impact. Read more at: http://healthitanalytics.com/news/healthcare-big-data-analytics-plays-critical-role-in-quality
The Internet of Things (IoT) is one of the most hot and debated issues in context of Big Data Analytics. It provides huge and enormous volume of data and reduces the cost of obtaining data significantly. It is estimated that within the next five years there will be more than 50 trillion gigabytes of data. The huge volume of data may provide valuable insights into the market and may be useful for development of technology related to business expansion. Sometimes it may be a challenge to handle such large volume of data and extract useful information out of it. But with rapid progression in technology, analyzing such data is becoming less difficult, and it importance in modern business practices is rising exponentially. Read more about this article at: http://www.content-loop.com/search-true-value-internet-things/
Yes, a $10 supercomputer swept Wall Street away. Braxton McKee, math and computer whiz, is tapping into the cloud to fetch all that market data inexpensively and built a software that employs Machine Learning algorithms to understand this data. Thanks to Cloud Computing and Big Data analytics getting cheaper, many startups and businesses can now employ their functionalities to provide services that are efficient, fast and scalable. The large amounts of data is mostly unstructured data, such as corporate documents, transcripts and social media and with the rise of Cloud Computing, the process is finally cost effective. Entities have begun leveraging cloud power to help hedge funds and other financial players run complex, big-data computer models. Maybe Cloud based Big Data analytics is the future. Read more at:http://www.smh.com.au/business/markets/10-hedge-fund-supercomputer-sweeps-wall-street-with-power-from-the-cloud-20150521-gh68hx.html
