Contact at or 8097636691/9323040215
Responsive Ads Here

Tuesday, 29 May 2018

Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate

Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data duration, search, sharing, storage, transfer, visualization, querying and information privacy. The term often refers simply to the use of predictive analytics and Analysis of data sets can find new correlations to "spot business trends, prevent diseases, and combat crime and so on. Projects on Big Data are growing rapidly because they are increasingly gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.

Characteristics of projects on Big Data
Big data can be described by the following characteristics

Veracity The quality of Data captured can vary greatly, affecting accurate analysis.
Volume The quantity of generated and Data stored. The size of the data determines the value and potential insight and whether it can actually be considered big data or not.
Velocity In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Variability Inconsistency of the data set can hamper processes to handle and manage it.
Variety Type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
Data must be processed with advanced tools (analytics and algorithms) to reveal meaningful information. For example, to manage a factory one must consider both visible and invisible issues with various components. Information generation algorithms must detect and address invisible issues such as machine degradation, component wear, etc. on the factory floor so these things we can study in Projects on Big Data.

for engineering students
 for Engineering Students

Engineering students should choose big data for his final year project, because it Big-Data is the future of modern data science. We have best 2018-2019 for engineering students ideas, which is going to be extremely useful in day to day life. At CITL you will get expert training for any kind of projects based on Big Data. Engineering students can do their Big-Data projects on these area

Real time data recovery, getting missing values
Social Marketing Footprint discovery and analysis for Marketing
Smart City Maintenance, and Data Management system 2018
Auto spelling and grammar detection and correction
Human Activity Recognition, Public Transport, Machine Learning
Cloud computing object storage and integration system
DNA Database storage and analysis
Real Time query answering system form Big Data Source