Big Data Research Papers
Big Data Research Papers focus on analyzing several analytics, methodologies & tools. It can be applied to big data. Big data research papers focus on analyzing the challenges in Big Data, and its available techniques.
Get the best Big data research papers pdf from the hands of highly experienced subject-matter experts.
An Introduction to Big Data:
Big Data will be the Big thing in the IT world.
Big data burst upon the scene in the first decade of the 21st century.
Firms such as Google, eBay, LinkedIn, and Facebook were made around big data from the beginning.
Big data can bring about dramatic cost reductions, substantial improvements in the time needed to accomplish a computing task, or new product and service aids.
What is Big data?
“Big Data” is similar to “Small Data” but it will be bigger.
There are numerous approaches need for big data. They are,
Big data is aims to resolve new or old problems in a better way.
Decoding the human genome originally took 10 years to be processed, and now it can be achieved in one week.
Three characteristics of big data V3s
VOLUME
Data quantity
VELOCITY
Data speed
VARIETY
Data types
1st character of Big data
VOLUME
A typical PC might have had 10GB of storage in 2000.
Today, Facebook consumes500 tetrabytes of new data every day.
2nd character of big data
VELOCITY
Clickstreams and ad impressions capture user behavior at millions of events per second.
High-frequency stock trading algorithms reflect market alterationswithin microseconds.
Machine to machine process will exchange of data between billions of devices
Infrastructure and sensors will createhugelog data in real-time.
Online gaming systems will support millions of concurrent users;each one will produce multiple inputs per second.
3rd character of big data
VARIETY
Big data is not just numbers, dates, and strings. Big data is also geospatial data, 3D data, audio and video, and unstructured text, which includes log files and social media
Traditional databases systems were formed to reportsmaller volumes of structured data, fewer updates, or a predictable, consistent data structure.
types of BIG DATA ANALYSIS
BIG DATA ANALYSIS includes various types of data They are,
- Storing Big data
- Selecting Big data
- Processing big data
SELECTING BIG DATA STORES
Choosing the correct data stores on the basis of your data characteristics
Moving code to data
Execution of polyglot data store solutions
Aligning business goals to the suitable data store.
STORING BIG DATA
Analyzing your data characteristics
- Selection of data sources
- Removing redundant data
- Establishing the role of NoSQL
Overview of Big data stores
- Data models: Key-value, graph, document, column family.
- Hadoop distributed file system
- HBase
- Hive
PROCESSING BIG DATA
Integrating disparate data stores
- Mapping data to the programming outline
- Connecting and removing data from storage
- Transforming data for processing
- Dividingdata in preparation for Hadoop MapReduce
Using Hadoop MapReduce
- Making the components of Hadoop MapReduce
- ImplementingHadoop MapReduce jobs
- Observingthe progress of job flows
The structure of BIG DATA
HISTORY OF BIG DATA
BIG DATA PHASE
BIG DATA PHASE 3.0
Thoughweb-based unstructured content is still the main focus for many organizations in data analysis, data analytics, and big data, the current possibilities to recovervaluable information are emerging out of mobile devices.
BIG DATA PHASE 2.0
Since the early 2000s, the internet and website have started to provide unique data collections and data analysis chances. With the expansion of web traffic and online stores, companies such as Yahoo, Amazon, eBay started to analyze the behavior of customers by analyzing click-rates, IP-specific location data, and search logs. This opened a completely new world of opportunities.
BIG DATA PHASE 1.0
Data analytics and big data, both terms were originated from the longstanding domain of database management. It depends onthe storage, extraction, and optimization methodologies that are common in data that will bestored in relation database management systems.
Applications of Big data analysis:
Used in smarter healthcare
Involves in Homeland security
Manufacturing
Traffic control
Multi-channel sales
Telecom
Trading analytics
Search quality
Disadvantages of Big data:
Despite the applications and advantages of big data, it has several disadvantages as well.
- Need for talented scientists and experts and highly paid workers in the IT field.
- Incompatible tools are needed. Hadoop is a highly useful tool in Big data, but the standard version of Hadoop is currently available to handle real-time analysis.
- Correlation errors- A common methodology that isutilized to analyze Big data. And that is available to draw correlations by connecting one variable to another.
- Security and privacy concerns: Big Data analytics will allowyou to detect fraudulent attempts.
our team is currently engaged with plenty of research paper projects such as in Artificial intelligence, Greenhouse, Thermal engineering , Water resource, Telecommunication , Biosensors, Antenna, Wireless Communication, Marketing , Finance, Accounts, Organizational behavior , Structural Engineering , NLP , Computer Security, IoT , Image Processing, Cloud Computing , Signal Processing, Microwave in Electromagnetic , Control System, Power Systems , HRM, Concrete based, And more.
© 2015 - 2024 Higs Software Solution. All Rights Reserved Powered By Tyekontech
Privacy Policy Download Brochure Terms & Conditions