Big data refers to the vast amount of structured and unstructured data that inundates organizations on a daily basis. This data comes from various sources such as social media, sensors, digital transactions, mobile devices, and more.
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Analysis on big data concepts and applicationsIJARIIT
The term, Big Data ‘ h a s been referred as a large amount of data that cannot be handled by traditional database
systems. It consists of large volumes of data which is been generated at a very fast rate, these cannot be handled and processed by
traditional data management tools, so it requires a new set of tools or frameworks to handle these types of data. Big data
works under V’s namely Volume, Velocity, and Variety. Volume refers to the size of the data whereas Velocity refers to the
speed that the data is being generated. Variety refers to different formats of data that is generated. Mostly in today’s world
thee average volumes of unstructured data like audio, video, image, sensor data etc. One can get these types of data through
social media, enterprise data, and Transactional data. Through Big data analytics, one can able to examine large data sets
containing a variety of data types. Primary goals of big data analytics are to help the organizations to take important decisions
by appointing data scientists and other analytics professionals to analyses large volumes of data. Challenges one can face
during large volume of data, especially machine-generated data, is exploding, how fast that data is growing every year, with
new sources of data that are emerging. Through the article, the authors intend to decipher the notions in an intelligible
manner embodying in text several use-cases and illustrations
Big Data Analytics: Recent Achievements and New ChallengesEditor IJCATR
The era of Big data is being generated by everything around us at all times. Every digital process and social media
exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming
velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics
capabilities and skills. Big data has become an important issue for a large number of research areas such as data mining,
machine learning, computational intelligence, information fusion, the semantic Web, and social networks. The combination of
big data technologies and traditional machine learning algorithms has generated new and interesting challenges in other areas
as social media and social networks. These new challenges are focused mainly on problems such as data processing, data
storage, data representation, and how data can be used for pattern mining, analysing user behaviours, and visualizing and
tracking data, among others. In this paper, discussion about the new concept big data and data analytic their concept, tools
and methodologies that is designed to allow for efficient data mining and information sharing fusion from social media and of
the new applications and frameworks that are currently appearing under the “umbrella” of the social networks, social media
and big data paradigms.
Big data refers to the vast amount of structured and unstructured data that inundates organizations on a daily basis. This data comes from various sources such as social media, sensors, digital transactions, mobile devices, and more.
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Analysis on big data concepts and applicationsIJARIIT
The term, Big Data ‘ h a s been referred as a large amount of data that cannot be handled by traditional database
systems. It consists of large volumes of data which is been generated at a very fast rate, these cannot be handled and processed by
traditional data management tools, so it requires a new set of tools or frameworks to handle these types of data. Big data
works under V’s namely Volume, Velocity, and Variety. Volume refers to the size of the data whereas Velocity refers to the
speed that the data is being generated. Variety refers to different formats of data that is generated. Mostly in today’s world
thee average volumes of unstructured data like audio, video, image, sensor data etc. One can get these types of data through
social media, enterprise data, and Transactional data. Through Big data analytics, one can able to examine large data sets
containing a variety of data types. Primary goals of big data analytics are to help the organizations to take important decisions
by appointing data scientists and other analytics professionals to analyses large volumes of data. Challenges one can face
during large volume of data, especially machine-generated data, is exploding, how fast that data is growing every year, with
new sources of data that are emerging. Through the article, the authors intend to decipher the notions in an intelligible
manner embodying in text several use-cases and illustrations
Big Data Analytics: Recent Achievements and New ChallengesEditor IJCATR
The era of Big data is being generated by everything around us at all times. Every digital process and social media
exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming
velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics
capabilities and skills. Big data has become an important issue for a large number of research areas such as data mining,
machine learning, computational intelligence, information fusion, the semantic Web, and social networks. The combination of
big data technologies and traditional machine learning algorithms has generated new and interesting challenges in other areas
as social media and social networks. These new challenges are focused mainly on problems such as data processing, data
storage, data representation, and how data can be used for pattern mining, analysing user behaviours, and visualizing and
tracking data, among others. In this paper, discussion about the new concept big data and data analytic their concept, tools
and methodologies that is designed to allow for efficient data mining and information sharing fusion from social media and of
the new applications and frameworks that are currently appearing under the “umbrella” of the social networks, social media
and big data paradigms.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.