Lakshman Mandalapu and Damini Thatha
Posters-Accepted Abstracts: J Comput Sci Syst Biol
While ?big data? has become a highlighted buzzword since last year, companies are now concentrating on more data to take informed decisions. Huge amount of investment is made in storing and processing large amounts of data to make better decisions. The term ?Big Data? is derived from the fact that the datasets are so large that typical database systems are not able to store and analyze the datasets. The processing of big data is done by using Map Reduce. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium-sized businesses. The discussion includes a review of state-of-the-art frameworks and platforms for processing and managing big data as well as the efforts expected on big data applications in science as well as in medical fields. We hope our effort will help reshape the subject area of today?s technology toward solving tomorrow?s bigger challenges emerging in accordance with big data. Big data is the term for a collection of data sets which are large and complex; it contains both structured and unstructured type of data. Data comes from everywhere, sensors used to gather climate information, posts to social media sites, digital pictures and videosetc. This data is known as big data.Big data concerns large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, big data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. The data model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. Big data, which refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology. Big data presents a grand challenge for database and data analytics research. The central theme of this talk is to connect big data with people in various ways. Particularly, the author will showcase his recent progress in user preference understanding, context-aware, on-demand data mining using crowd intelligence, summarization and explorative analysis of large data sets, and privacy preserving data sharing and analysis in Research and Industry.
Lakshman Mandalapu chowdary is currently doing his graduation in engineering stream from Rise Krishna Gandhi Group Of Institutions.
Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report