What is Big Data a Study Guide for Phd Students
What is Big Data a Study Guide for Phd Students
Understanding the term Big Data and gaining wisdom on it
For the past decade, the word “Big Data” has been used widely among tech enthusiasts and in the field of information and communication technology. For those who might wonder, it is simpler than it sounds.
Though the term Big Data is obvious in its attribution, but if you still find it challengint to comprehend it, this guide will make you want to explore Big Data to the fullest extent. Know the foundations of Big Data on a complete scale and its significance—a comprehensive guide to understanding Big Data.
The most repeated question is, what exactly is Big Data?
The terminology Big Data literally means the very nature of it. The large sets of data that are stored, analyzed, and concluded by an algorithm on a computing resource is the primary concept of Big Data. It derives insights from simulations based on real-life events that are not practically possible to experiment with, such as weather forecasting, genomics, etc. These large or complex data sets are beyond the capabilities of conventional data processing techniques. These large data sets often require a highly efficient computational model that can handle the 3Vs of Big Data.
The 4V’s of Big Data
- One of the qualities that defines Big Data more exactly is the 4Vs of Big Data -Volume, Velocity Variety & Veracity.
- Volume is the key factor in deciding whether it is Big Data or not, as the quantity of the data is directly proportional to the accuracy of the outcome.
- The average size of big data is ten times bigger than that of traditional data.
- The function that makes big data preferable to traditional data is the speed of outcome, which is essential in certain sectors where there is a huge need to predict risk, such as Finance, Healthcare, etc.
- As it generates and manages large data in real-time with higher accuracy, Velocity in Big Data became a key attribute.
- The next V is Variety. Without depending on a single source, Big Data obtains data generated among diverse sources that mostly tend to be semi-structured or unstructured.
- Their ability to handle these unorganized data contributes to the practical applicability of this concept.
- The recent V of Big Data is Veracity, which is the reliability of the data. They must be reliable in terms of their quality, which plays a decisive role in the accuracy of the outcomes.
- Confidence and trust that can be given to the data is a high concern as it can lead to lower accuracy rates if the data has no proper credibility.
- The more meaningful the data is, the more valuable the insights will be.
Common Challenges of Big Data
Integration
Combining data from various sources with varying formats requires a tough system that ensures the seamless integration of these data, which will smoothen the computational process and enhance efficiency. Hence, such a framework is demanded.
Scalability
The ever-increasing volumes of data further increased the complexity and scalability of these data models; therefore, it became crucial to maintain data scalability to keep the efficiency stable and uninterrupted.
Data Security
Protecting the data from being breached or misused has unavoidably emerged as a great concern to ensure compliance and trust issues At the same time, keeping such huge amounts of data obtained from diverse sources is a challenging task.
Applicability of Big Data
Decision Making
Rather than making decisions in an old-fashioned way, Big Data will enhance the process of Decision-making with its accurate ability to analyze patterns and find trends.
Customization
These data processing models can be customized to specific needs, making them more flexible and versatile. This adaptability of big data leads to collective improvement in all sectors.
Risk mitigation
These computational models allow us to anticipate future events and derive insights and predictions with higher accuracy rates even before they occur, detecting potential risks before they arise. This capability of Big Data is often praised as one of the pinnacles of data analysis.
Recent Applications
Banking and Security Industries
Big Data is being used by the SEC [Security Exchange Commission] to monitor financial activity and uses it to mitigate risks involved regarding illegal and unethical practices.
Healthcare sector
Historical data from previous patients is utilized to develop evidence-based treatment and predictive analytics. The University of Florida utilizes public patient data to generate graphics for speedier identification.
Big Data in Education
The University of Tasmania utilizes big data to a great extent in its educational system. Such is the case with the University of Tasmania, which is an Australian institution with a student population of more than 26000 that has adopted a Learning and Management system to track activity when they log in the system, how much time is spent on different sites within the system, and overall progress over time, among other pieces of information.
Conclusion
Big Data has transformed in so many ways in multiple aspects on a broad scale, as the practical usage of this concept is well established in certain fields.Whereas in other fields, this can be implemented effectively by eliminating the challenges through fine and extensive research.Researching in the sense of doing a thesis or a dissertationcan open gates for numerous prospects in the field of Big Data.These can be well explored with our expert assistance,who has proper sources of knowledge and years of expertise.Order your package and follow your passion in the right
References
https://www.sec.gov/newsroom/speeches-statements/bauguess-big-data-ai
https://guides.uflib.ufl.edu/precisionpublichealth/datalibrary