Predictions for Big Data

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Data are flooding in at rates never seen before—doubling every 18 months—as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities and newly deployed smart assets. These trends are broadly known as “big data.” Technology for capturing and analyzing information is widely available at ever-lower price points. But many companies are taking data use to new levels, using IT to support rigorous, constant business experimentation that guides decisions and to test new products, business models, and innovations in customer experience. In some cases, the new approaches help companies make decisions in real time. This trend has the potential to drive a radical transformation in research, innovation, and marketing- According to Mckinsey & CO.

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Predictions for Big Data

  1. 1. Predictions for Big Data Data are flooding in at rates never seen before—doubling every 18 months—as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities and newly deployed smart assets. These trends are broadly known as “big data.” Technology for capturing and analyzing information is widely available at ever-lower price points. But many companies are taking data use to new levels, using IT to support rigorous, constant business experimentation that guides decisions and to test new products, business models, and innovations in customer experience. In some cases, the new approaches help companies make decisions in real time. This trend has the potential to drive a radical transformation in research, innovation, and marketing- According to Mckinsey & CO. IDC predicted the Big Data market will grow to $ 16.1 billion in 2014 and they also forecast that the Big Data technology and services market will continue to grow at a 27% rate to $ 32.4 billion through 2017. Source: International Institute of Analytics IIA
  2. 2. Predictions for Big Data Enterprises will combine computing resources for a better Big Data solution According to Adaptive Computing’s survey, 91 percent of organizations believe some combination of Big Data, HPC (High Performance Computing) or cloud should occur. Organizations will gain a competitive advantage by investing in software capable of scheduling and optimizing data center resources, which increases utilization by simultaneously orchestrating compute jobs over multiple computing platforms. Big Data analysis process will become more automated The majority of organizations (84 percent) have a manual process to analyze Big Data. A manual approach is time-consuming and typically results in underutilized, siloed computing environments, which explains why 90 percent of survey respondents would achieve greater satisfaction from a better analysis process or workflow. More efficient Big Data analytics will increase revenue streams Research published by Gartner in January 2014 titled "User Survey Analysis: Driving Efficiency and Reducing Cost Is King When It Comes to Decision Making for New Technology Solutions" found that "mobility, Big Data and analytics were rated as being of greater importance to an organization’s strategy than social." "This aligns well with the data received from a recent vendor survey conducted by Gartner in which 2,015 providers expect analytics to account for three times the revenue stream of social The rise of the Internet of Everything (IoE) The rise of the Internet of Everything (IoE) will affect the industrial sector dramatically. By 2020, 40% of all data will come from sensor data and it will unlock a $ 1 trillion global market in 2020 (currently it is a $ 121 billion global market). In addition, GE reports that the Internet of Everything (IoE) could add $10 to $15 trillion to global GDP in the coming years. Big-Data-as-a-Service solutions Big-Data-as-a-Service solutions, will help organizations apply Big Data techniques, without the heavy costs involved. Especially useful for Small or Medium sized enterprises who do want to develop a data-driven information-centric organization, but who do not have the capacity to develop and maintain a full-fledge Big Data solution on premises. Big-data-as-a-Service is a combination of Analytics-as-a-service, Infrastructure-as-a-Service and Data-as-a-Service and it will spur the adoption of Big Data also by smaller and medium sized organizations.
  3. 3. Security to protect the privacy Organizations will start to focus more heavily on securing their data to protect the privacy of their customers. More and more organizations will start to use Big Data techniques to secure their IT infrastructure and prevent from being hacked and have data monitored or stolen. Log data will form an important aspect in this and organizations will start to see the importance in monitoring and analyzing their IT infrastructure log data in order to keep their infrastructure and data safe. This will help to restore and keep the trust of their customers. Personalization will become personal Consumers are creating massive amounts of data through every click, like, tweet, cell-phone call, purchase and self-tracking applications they use. Companies like Amazon have already used these kinds of data for many years to create a personal online shopping experience with recommendations, personal homepages, personal discounts or personally targeted mass-email campaigns. Personalization is making a giant leap forward in the coming years. Consumers will start to see that their data is valuable and they do want something in return for providing their data. So consumers are willing to cooperate and share their data if it brings them personalized discounts. Education will be essential for success As more organizations are trying to understand Big Data and preparing their staff for the Big Data era, education becomes a crucial aspect. Already in 2011, McKinsey predicted a shortage in the coming years of Big Data scientists and Big Data managers. Organizations will therefore stimulate their employees to be more Big Data skilled. Many organizations are heading for a major skill gap and will have to take action to be ready for the big data era. Also fresh-graduates or students will see the Big Data trend and in the competitive jobs market will feel the need to differentiate to stand a chance on the job market. Big data moves into mixed data In the past years Big Data was all about obtaining as much data as possible and the perception was that you require massive datasets to gain insights from those data sources. In the coming years however, organizations’ will start to see that the most important aspect of Big Data is not so much the volume of a dataset, but more the insights derived from combining several, smaller, datasets. They will start mixing and combining several data sets that they will analyze to derive insights. References: http://www.knowesistech.com/wp-content/uploads/2013/06/what-is-big-data.jpg http://www.cio.com/slideshow/detail/132163#slide2 http://www.brightplanet.com/2014/02/2014-trend-prediction-daas/ http://whatsthebigdata.com/2013/12/16/2014-big-data-predictions-from-idc-and-iia/
  4. 4. http://www.theguardian.com/technology/datablog/2014/jan/14/big-data-4-predictions-for-2014 http://www.bigdata-startups.com/big-data-trends-2014/ http://www.mckinsey.com/insights/high_tech_telecoms_internet/clouds_big_data_and_smart_as sets_ten_tech-enabled_business_trends_to_watch http://blogs.gartner.com/anton-chuvakin/2013/12/03/gartner-predicts-2014-out-and-one-on-big- data/ http://www.itbusinessedge.com/slideshows/top-predictions-for-big-data-in-2014-02.html

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