On :August 7, 2018
Big Data is being created every day with the main interaction of billions of people using their computers, GPS devices, cell phones, sensors and medical devices which are using it more effectively. Many analytical companies which are engaged in finding the hiding information from Big Data. According to all the internet experts and the advanced technological assets, an analyze the massive amount of data flood which will lead to the revolutionary changes in the industry and the society. As of today’s, a lot of work to be done by the tools and software. All the Big Data applied organizations are been give an attention for the development of data analytics in many departments like education, healthcare, information technology, aerospace, etc.… for the benefit of the society. A 4.0 factory, machines are major connected to collaborative the community.
All the communities such requires advanced prediction tools so that the data can be systemically processed into the information which explains the uncertainty which can make more informed decisions. All the leading unprecedented levels of the business intelligence will always be concerning the habits of all the rivals. However, Big Data is not straightforward and it might seem to the particularity when it comes to the bulk of the data from the social media. This sets will always seem to be offered the prospect of getting access to the forms of knowledge which are previously Insight to which were once thought as difficult. This paper mainly addresses the trends and the impacts of the Big Data in today’s flood of data in all the network technologies.
In today’s competitive business environment all leading companies are facing many challenges in dealing with many issues on the Big data on the rapid changes in the data floods. Major many manufacturing companies are not ready to manage their data due to lack of smart technology tools. As more software and embedded technologies are into the intelligence which is integrated into many industrial products and systems.
All the predictive technologies which are further intertwined with all the algorithms. Nowadays all smart factories are being mainly focused on the control-centric optimization and intelligence. The amount of data which was available for them for their business to increase exponentially with social media and machine-to-machine with all the leading sources. The truth is that many organizations which are already successfully harnessing the power of the data are being transformed to Big Data.
E-Commerce and Market Intelligence
The excitement surrounding of Big Data has been arguably been generated from the web and e-commerce communities. Significant market transformation is being established like Amazon, eBay is leading the highly scalable e-commerce platforms and the product recommender systems. Major internet platforms such as Google, Amazon, Facebook which always continue to lead the development of web analytics, cloud computing, and social media platforms.
The major emergence of Web 2.0 content on the various forms of the newsgroup and social media platforms and the crowdsourcing systems always offers another opportunity for researchers and the practitioners. These are used to listen to the voice of the market from the enormous number of business fluctuations including customers, employees, investors and the media. All the traditional records which are been collected from 1980’s the data that e-commerce systems are used to collect from the web are been less structured which often contains rich consumer opinion and behavioral information.
According to social media analytics of customer opinions and the text analysis and the sentiment analysis are the major techniques which are frequently adopted by “Pang and lee in 2008”. Various analytical systems are also developed for the product recommender systems such as then database segmentation and the clustering. Long Tail marketing which was accomplished in reaching to millions of niches market at the shallow end the of the product bitstream will become most possible via highly targeted searches and personalized recommendations.
The Netflix price competition in the best collaborative market of filtering algorithm to predict the user move ratings which has been helped to generate the significant academic and the industry interest in recommender systems. The development of the recommender system and has been awarded as the grand prize of$1 million to the Bellkor’s Pragmatic chaos team, which has surpassed Netflix’s own algorithm in the presiding ratio of 10.6 percent. In this, however, the publicity which was associated with the competition and raised according to the customer privacy concerns.
Trends and unmet needs for Industry 4.0 era
Discovering of innovative technologies has emerged which has escorted the industry development from the early adoption of all the mechanical systems to support the production process. In today’s highly automated assembly lines which order to be responsive and adaptive to the current dynamic market requirements and demands. Under the industry concept, astounding growth in the advancement and the adoption of information technology and the social media networks which rapidly increased has mainly influenced the customers, which mainly leads to the project innovation and quality and the speed of delivery. This will mainly require the establishment of the factory with the capabilities of self-awareness, self-prediction, self-comparison, and self-maintenance.
Many advanced countries whose economy is always based on the manufacturing industry which has tried to transform their economy and reinvigorate the industry. Servitization was proposed by Vandermerve and Rada in 1988. Servitization is defined as the strategic innovation of an organization’s capabilities which processes to turn from selling products. The concept of the product service system(PSS) is the major special case of servitization. Industrial Big Data environment is a boost for the social network. This is also called as the web2.0 Era since late 2004. Most of them have been focused on the social or commercial mining. This will mainly include the sales prediction and the relationship between mining and clustering.
E-Government and Politics
In 2008 The U.S. House, Senate, and the presidential election have provided the first signs of success for the online campaigning. Politicians use the highly participatory and multimedia and the multimedia we platform for all the successful policy discussions, campaigning, advertising, event announcements and online donations. As we know that the government and the political parties are becoming more transparent, participatory, online, multimedia-rich, which has a terrific opportunity for adopting the BI& A Research in the e-government and politics. Some of the social media analytics and the social network analytics can be majorly used for the support of online political participation.
In the last decade, Web analytics has been merged into an active field of research. Building on the data mining and statistical analysis foundations of data analytics and the information retrieved from the NLP models in any of the text analytics which offers a unique analytical challenge and the opportunities. HTTP/HTML based hyperlink websites are associated with any of the search engines and the directory systems which will help them to find the unique internet-based technologies for website ranking, search engine updates, and log analysis.
Weblog analysis is mainly based on the customer transactions which were subsequently turned into active research and recommender systems. In the mid-2000’s web analytics has become more exciting with the maturity and popularity of web series. Based on all the XML and Internet Protocol (IP) web services started to offer a new way of refusing and integrating all the third-party systems. The major emerging component in research of web analytics has developed the platforms and services of cloud computing which includes applications, software’s, hardware, which was delivered over the services through the internet.
The manufacturing sector has come so flat in the use of data and analytics which are not far enough. According to MIT professor Eric Byrnjolfsson which was written on this month “Too many managers are not opening their eyes to this opportunity and understanding what Big Data can do to change the way they compete”. All manufacturers who don’t have a long-term in the historic vision will always be more significant to its disadvantage of their competition. This will become a reliable supply to their chain partners…