• Manjunatha Swamy C
• Dr.S.Meenakshi Sundaram,
• Dr.Lokesh M R

In Big data analytics information extraction and classification plays vital role to process the data in batch mode and in stream mode to support this mode of analysis and processing must require architecture. Architecture is backbone of any application to work successfully it handles data ingestion which collects large data and files generated from different sensors and actuators into storage medium which further represented in report using modern tools. There are many architectures have been introduced from industry and academics, universal acceptance of these approaches for other types data analysis is not feasible. Some architecture solutions are not standard big data processing architectures. In this work we proposed smart Big data architecture to extract information and analyze the performance of information extraction using layered approach model to address data collection, processing, storing and data reporting and visualization of large data both in batch mode and real stream mode. Proposed work shows significant improvement with other architectures.

Big data architecture, Feature extraction, Feature classification, Data analysis and Storage, Data visualization, EBBA model, PIMM model.

"Evaluation of Information Extraction Architecture in Big data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.d677-d686, April-2023, Available :http://www.jetir.org/papers/JETIR2304396.pdf

"Evaluation of Information Extraction Architecture in Big data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppd677-d686, April-2023, Available at : http://www.jetir.org/papers/JETIR2304396.pdf