Business Intelligence Application Development
#Q.1
Business Intelligence refers to many technologies and strategies that have been laid down by the entity in the analysis of data relating to the business. They are the practices that relate to integration, analysis, collection, and presentation of data (Audzeyeva & Hudson, 2016). For instance, BI implementation in Amazon helped the company to increase its marketing and sales. As well, it helps to keep track of information relating to clients, which helps to look at customer issues.
#Q.2
The factors that should be implemented in the cost-benefit analysis are payback period and anticipated benefits (Mousa et al., 2018). Amazon should consider BI to bring forth massive benefits to the entity and identify the time that it will take to pay back the amount invested.
#Q.3
The level of granularity in the design is high because there is a coherence and sufficient flow of information.
The advantage of granularity is that it aids in examining brand performance by making various adjustments to the discrete variables (Audzeyeva & Hudson, 2016). The disadvantage is that granularity does not necessarily help in better decision making. This is because it becomes challenging to synthesize particular information.
#Q.4
Transformation takes 80% ETL because data is gotten from the online transactions (Mousa et al., 2018). For instance, transactional databases of Amazon are easily aligned towards goal achievement.
#Q.5
Slice and dice is the ability to manipulate big data and apply SUM and COUNT summaries (Audzeyeva & Hudson, 2016). Drill down/up helps the users to see data in a detailed fashion.
#Q.6
Data processing helps in ensuring better decisions are made, which are more reliable and accurate (Mousa et al., 2018). Techniques used in data processing are conversion, validation, sorting, summarization, and aggregation.
#Q.7
What should be changed in the graph is the scale, structure, and formation. The scale should be changed to enhance coherence and systematic nature. The structure should show the relationship that exists between online hotel and revenue (Audzeyeva & Hudson, 2016). Lastly, the formation should be adjusted where necessary for easy understanding.