Scope of Big Data Applications
Every day, we produce 2.5 quintillion bytes of data, so much that 90% of the data in the world today has been created in the last two years alone. The data which comes from different sources are converted into useful information’s by using big data analytics. These large amount of data that is being produced continuously is what can be coined as Big Data. Big Data Analytics open up extensive kind of openings in several fields.
Big Data Analysis substantially involves logical styles of big data, methodical armature of big data, and big data mining and software for analysis. Data accession is the most important step in big data, for exploring meaningful values, giving suggestions and opinions. Possible values can be explored by data analysis. And also these collected data’s should be useful for the analysis.
In olden days companies used to advertise their product for marketing. But in that there is no much targeted approach . But now a days companies are substantially used digital marketing for their product’s promotion. In digital marketing with the help of these big data operations it’s easy to target the right leads for the business.
APPLICATIONS OF BIG DATA
- Market the product to right audience
- Fraud Detection and risk management
- Supply chain Management
- Direct Innovation and product development
Challenges in Big Data Applications
In Big data projects, the foremost important thing is the data itself. With these data, only organizations are making their predictive models for their unborn systems. So If we miss any data while collecting from all scenarios it may beget a massive negative impact on decision making. That is if we missed any data while collecting data or if we get any wrong input while data analysis we will be getting wrong predictive models and it may cause us of making wrong decisions. This is one of the main challenges faced in big data analysis. Big data is a significant area which offers numerous benefits and innovations. It’s a
remarkable sphere with a promising future, if approached rightly. The difficulty with big data
comes substantially from its size, which requires proper storehouse, operation, integration, sanctification,
processing, and analysis.
Characteristics of Big Data
Types of Big Data
Types of Big Data
