Advantages and Disadvantages of Big Data
Experts predict that Big data analytics will be the game-changer in the Business, Consumer market, and society. Where tech giants like Google, Oracle, and IBM dig into the research, data scientists have already speculated Bog Data's potential benefits. These Advantages and Disadvantages of Big Data explore further to find out its pros and cons from different viewpoints.
What is Big Data?
What comes next to Terabytes? It’s Petabyte and Yottabyte. Imagine the data that can take up this much space and can only be handled through machines. Data management is probably the key to open solutions to manage real-life problems with more efficiency.
But, unfortunately, traditional software and programs face issues and are not capable of processing voluminous information. The analysis of all the data and extracting useful information out of it is called big data analytics.
A large amount of data is generated every second and mounts up unless used to give productive conclusions. Most of the data is random. The usefulness of this information processing software is needed to provide you with insight into the bulk information and predict future results and possibilities.
It can give helpful analysis based on which future goals can be set. Of course, with voluminous information will come machine learning and, eventually, numerous applications of Artificial Intelligence.
What are the Advantages of Big Data?
The analysis of present situations and acting accordingly is how business works take the IT Industry, for example. This makes data analysis a crucial part of achieving business goals. It helps in lowering the investment and reduces faults in the current mode of operation. The advantages of Big Data Analytics below show and how retrieving information and collecting data is useful.
1. Voluminous Collection
A large amount of market data can be generated using Big Data analytics, and various graphical and mathematical representations can be made for easy analysis. This massive information is further helpful for deriving market-based conclusions and predict consumer behavior. However, new technology needs to ramp up in this field as traditional software cannot process big data.
2. Future Insights are mentionable Advantages of Big Data
With the predictions and statistical data obtained, a business can control prospects. The growth and future problems of a business can be well handled using this analysis. Using these datasets, a company can plan its launches also create new products and services. Scientists foresee the same benefits of Big Data analytics in the healthcare industry and societal affairs.
3. Big Data Analytics is Cost Efficient
It is essential to understand the changing trends of the market and to do that, a market analysis needs to be done. At a particular time, a specific direction is followed while others are remaining constant or decreasing. A business is all dependent on the actual demand, and if they can predict it, they can have control over the production. It can save costs incurred in storing raw material and finished products.
4. Research will take less time
New software can easily analyze and interpret data sets, which helps make decisions and saves a lot of time. Also, new data can be generated automatically in bulk with updated information and trends. This can help businesses to stay stable in the long run.
5. Fraud Detection and Prevention
Big Data is capable of stopping fraudulent transactions, as in the case of banking services. The frauds are getting smarter, and people need to know not to share personal information; the automated software can detect fraudulent accounts and cards. Based on recurring patterns and the spending behavior of consumers, it would also be possible to track what's usually missed manually.
What are the Disadvantages of Big Data?
Since all the information collected requires a lot of effort and resources, storing it before it can be examined needs a vast space. Although the analysis of enormous information seems possible, some significant disadvantages of Big Data come to light in terms of space, cost, and user security.
1. Unstructured Data
The data collected can be arranged or present in the form of random information. More variations in data can create difficulty in processing results and generating solutions. If the information is broken or unstructured, many users can get neglected while deriving future outcomes or analyzing present scenarios.
2. Security Concerns are most dreaded disadvantages of Big Data
For highly secured data or confidential information, highly secured networks are needed for its transfer and storage. Furthermore, with the increased global politics and complex situations between nations, leaked data can be used as an advantage by enemies, so keeping it secure is essential and requires building such a network.
The process of data generation and its analysis is costly without the surety of favorable results. The top businesses can mainly research this field as the space sector, where the wealthiest companies and individuals carry out research. The Cost of setting up super-computers is one of the leading disadvantages of Big Data analytics. Even if the cost is incurred somehow, the information usually residing on the cloud has to be arranged for and will require maintenance.
4. Skilled Analysts
The professionals needed to carry out research and run complicated software are highly paid and hard to find. There is a scarcity of individuals skilled for the data analyst job despite the increasing scope in this area of knowledge. Data is the resource of the new generation as to remain in the market; it is necessary to keep yourself updated with further information.
5. Hardware and Storage
The servers and hardware needed to store and run high-quality software are very costly and hard to build. Also, the information is available in bulk with continuous changes, and processing requires faster software and applications. And we cannot forget the uncertainty involved with getting accurate results.
Conclusion on Pros and Cons of Big Data
Assessing the Pros and cons of Big data analytics, it's clear the future technology has to be ready to deal with bulk information. Although data management and its analysis are needed for the new business models, its usefulness still needs better technology. Improvement in research techniques and algorithms capable of processing more accurate results is required. The redundancy of data due to global variations is also one of the common disadvantages of big data scientists are likely to face, and creating an AI-based model is still impossible. But there is possible in Impossible.