The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Comparing Big Data Analysis Techniques
Abstract
Big data refers to the large volume of data which can be processed to get the relevant, required, and meaningful data within less time. It is required to apply sophisticated methods and techniques to process big data. There are many methods and techniques available, like regression analysis, time series analysis, sentiment analysis, descriptive analysis, predictive analysis, association analysis with sampling, machine learning, visualization techniques, classification, and qualitative and quantitative analysis. In the future, there is a need to enhance the performance of these techniques due to increasing size of data. Many applications are based on any of these techniques to process the large volume of data in order to retrieve the meaningful data. It is expected, big data analysis techniques will filter and process the large volume and find the relevant one. Analysis of big data is very helpful in many areas like businesses, industries, and other sectors.
Related Content
|
Dina Darwish.
© 2024.
48 pages.
|
|
Dina Darwish.
© 2024.
51 pages.
|
|
Smrity Prasad, Kashvi Prawal.
© 2024.
19 pages.
|
|
Jignesh Patil, Sharmila Rathod.
© 2024.
17 pages.
|
|
Ganesh B. Regulwar, Ashish Mahalle, Raju Pawar, Swati K. Shamkuwar, Priti Roshan Kakde, Swati Tiwari.
© 2024.
23 pages.
|
|
Pranali Dhawas, Abhishek Dhore, Dhananjay Bhagat, Ritu Dorlikar Pawar, Ashwini Kukade, Kamlesh Kalbande.
© 2024.
24 pages.
|
|
Pranali Dhawas, Minakshi Ashok Ramteke, Aarti Thakur, Poonam Vijay Polshetwar, Ramadevi Vitthal Salunkhe, Dhananjay Bhagat.
© 2024.
26 pages.
|
|
|