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Predictive Analytics with Data Visualization
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There has been tremendous growth for the need of analytics and BI tools in every organization, in every sector such as finance, software, medicine and even astronomy in order to better overall performance. C-factor Computing has the same vision of empowering their existing products through data analysis and forecasting to better suit the need of customers and decision making of stakeholders. The project involves 5 key aspects in Analytics - Data Acquisition, Big data or data Storage, Data Transformation (Unstructured to Structured), Data Wrangling, Predictive Modeling / Visualization. Data Acquisition involves gathering existing transactional and search data of customers and travel aggregators who use the product. This data is used to create powerful dashboards capable of predictive analytics which help the company make informed choices. The key aspects mentioned can be achieved through various tools available but requires testing at every stage in order to realize the appropriate software for the data present in the company. Hence the project deals with studying and implementing selected tools in order to provide the right framework to achieve an interactive dashboard capable of predictive analytics which can also be integrated into the existing products of the company.
Inventive Research Organization
Title: Predictive Analytics with Data Visualization
Description:
There has been tremendous growth for the need of analytics and BI tools in every organization, in every sector such as finance, software, medicine and even astronomy in order to better overall performance.
C-factor Computing has the same vision of empowering their existing products through data analysis and forecasting to better suit the need of customers and decision making of stakeholders.
The project involves 5 key aspects in Analytics - Data Acquisition, Big data or data Storage, Data Transformation (Unstructured to Structured), Data Wrangling, Predictive Modeling / Visualization.
Data Acquisition involves gathering existing transactional and search data of customers and travel aggregators who use the product.
This data is used to create powerful dashboards capable of predictive analytics which help the company make informed choices.
The key aspects mentioned can be achieved through various tools available but requires testing at every stage in order to realize the appropriate software for the data present in the company.
Hence the project deals with studying and implementing selected tools in order to provide the right framework to achieve an interactive dashboard capable of predictive analytics which can also be integrated into the existing products of the company.
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