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Prominent Terminologies In The Business Intelligence Process In Data Science
In the present days’ competitive world, to stay competitive, most of the enterprises in the Business sector are relying heavily on Data Science to empower their Business Intelligence process. Business Intelligence process with Data Science can help the stakeholders in better understanding their business performance & also helps them in making accurate data driven smart business decisions. The Business Intelligence process with Data Science involves different techniques like Business Analytics, Data Mining, Data Visualization, Data Storytelling, Data Tools & other practices
By deploying accurate Business Intelligence models, analysts can help the business stakeholders & managers in identifying inefficient processes; predict threats & market trends, know their customer’s interest, etc & empowers them in making decisions accordingly.
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Now, let’s look at the prominent terminologies that are related to Business Intelligence process in Data Science.
Terminologies In Data Science Business Intelligence Process:
- Data Mining
It is a sequential process that relates to the use of statistical models & algorithms in Machine Learning to extract insights from Big Data to find hidden patterns & detect trends.
The findings from Big Data are communicated to business stakeholders & mangers who will be making accurate decisions based on these insights.
- Performance Metrics
The performances of different business processes are carefully analyzed against the historical data.
- Descriptive Analytics
Descriptive Analysis is performed to know why business processes are underperforming or why they aren’t able to achieve their desired goals.
- Data Visualization
The process of interpreting the results from the Big Data analysis to the stakeholders & managers in the form of attractive visuals & graphs using tools like Tableau
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