Citation International is organizing an International Conference on Big Data Analytics to be held in Spain September 17-19, 2018.The main theme of these conference is to escalate the new researches about Big Data Analytics and evolution taking in the future in development .The objective of this conference is to provide knowledge to the students to share the knowledge about the development and technologies implementing in Big Data Analytics by the researchers and scientists share the innovative ideas for the improvement in Big Data Analytics to provide better service for the participations . We would like to invite and be a part of this conference it will be a good platform to gain knowledge in the Big Data Analytics to the attendees. You’ll be inspired by means of pinnacle speakers and innovators inside the area who will proportion new ideas to recharge your profession; you’ll get to satisfy and talk with contributors of the own Big Data Analytics editorial board and other leaders.
Why to Attend??
Big Data Analytics 2018 invites attendees from around the world focused on learning about Big Data Analytics, this would be one of best opportunity to reach the largest assemblage of participants from the Big Data Science community. Conduct demonstrations, distribute information, meet with current and potential customers, make a splash with a new product line, and receive name recognition at this 3-day event. World renowned speakers, the most recent techniques, tactics, and the newest updates in Data Mining fields are hallmarks of this conference.
Importance and Scope:
The Aim of this Conference is to bring together researchers and practitioners to look deeper into how Semantic Web technologies can contribute towards Big Data analytics. This can be achieved either by extracting value out of these data (through reasoning), creating sustainable ontology models, offering a solid foundation for deploying learning techniques or anything in between.
Recent advances in availability of information on the Internet, storage space and web generated content have paved the way for the advent of Big Data. The well-known 4 Vs (Velocity, Variety, Volume, Value) that characterize Big Data can find a match in intelligent ways for management, manipulation and value-extraction. It is widely acknowledged that the recent upheaval in AI and especially machine learning is exactly due to these advancements. The Semantic Web can offer a well-studied, although ever advancing, toolbox that can address Big Data requirements and contribute towards their meaningful analysis. Still, there are often issues that need to be tackled with like bootstrapping, efficiency and standardized business processes for semantic analytics to achieve satisfactory results. To this end, machine- and deep-learning techniques, while being considered the poor relation for years, have been shown to have considerable contributions towards Big Data analytics and to overcome Semantic Web inherent limitations.
The Big data analytics market is projected to grow from USD 6.71 Billion in 2016 to USD 40.69 Billion by 2021, at a CAGR of 43.4% between 2016 and 2021.
The objective of the research study is to provide detailed segmentation of the Big data analytics market on the basis of component, application, vertical, and region. It also aims to provide information regarding key factors influencing market growth, and strategically analyze sub segments with respect to individual growth trends, future prospects, and contribution to the total market. The report helps analyze opportunities in the market for stakeholders, provide strategic profiles of key market players to comprehensively analyze core competencies, and draw a competitive landscape of the market. The base year considered for the study is 2015 and the forecast period is from 2016 to 2021.
The research methodology used to estimate and forecast the Big data analytics market begins with obtaining data on key vendor revenues and the market size of individual segments through secondary sources, such as annual reports, press releases, investors’ presentations, white papers, and paid databases, which include Factiva and Bloomberg, among others. Vendor offerings are also taken into consideration to determine market segmentation. The bottom-up procedure was employed to arrive at the overall size of Big data analytics from the revenue of key players (companies) present in the market.
After arriving at the overall market size, the total market was split into several segments and sub segments, which were then verified through primary research by conducting extensive interviews with key industry personnel, such as CEOs, VPs, directors, and executives. Data triangulation and market breakdown procedures were employed to complete the overall market engineering process and arrive at the exact statistics for all segments and sub segments.