Big data challenges stimulate with AI applications


Artificial Intelligence is a fast-growing technology that simulates human intelligence processes by machines. AI work by combining large set data and uses efficient algorithms to solve any critical problems. Big data refers to the collection of data in huge size and grows with time. Big data is linked with artificial intelligence, the development of big data technology depends on artificial intelligence since it uses many artificial intelligence theories and methods.

Big data is confidential information storage of a firm that contains data in huge size either structured or unstructured data of day to day business activities. The big data storage is spread across various computers as a single system, it is impossible to manage such a huge data set. Big data is considered as a reliable and useful source since it can be analyzed with AI applications. This analysis can do future predictions take decisions which in turn helps to boosts the company’s revenue.

Data seems one of the important sources of an organization but at the same time firms face a lot of challenges from this Big data:

1)Storage of data becomes complicated while maintaining it because most of them are duplicate data sets.

2)It is very difficult to maintain a high frequency of data.

3)Storage of data in a single repository never seems good which may give rise to complexity.

4)It is very difficult to differentiate data and put them in various channels.

Since data is one of the essential factors of any firm we need to solve all the issues from Bog data. For that, we can combine Big data with the latest AI technology applications.

The first step is we can filter data and put them in diverse files of relevant data sets. These offer to neglect the duplicate data sets and filling the gap of unavailable data.

 AI-based predictive maintenance can be applied for analysis, with source data sets we can identify failure points and error code.

Big data can ask help from data science which is an expert in analysis and prediction making. Various   Machine Learning algorithms are available for data scientists today, where they can seek help.           

Machine learning algorithms are also of great use as it facilitates the need to receive new data, generate outputs, and have some actions or decisions be made based on the outputs.

Big data issues like bad clarity content, unstructured data can be solved by arranging data in proper formats buy adopting suitable methods by company.

With the implication of these emerging solutions through AI technologies, a business that faces challenges in big data gets a solution.


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