MSP Bank, Limited is a leading varied Japanese monetary institution that provides a full range of financial products and services to both institutional and individual customers.
It is headquartered in Tokyo.
MSP Bank is hosting their existing infrastructure on AWS.
MSP bank has many segments internally and they are planning to launch a self-data discovery platform running out of AWS on QuickSight. Using QuickSight, multiple datasets are created and multiple analyses are generated respectively.
The Team is working on visuals.
Team wanted to build some charts on a single dimension, grouped dimensions against a single measure and multiple measures and their aggregations and summaries based on X and Y dimensions.
How can we achieve? Select 2 options.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: A, B.
Option A is correct - A bar chart visual type is used to create a single-measure, multi-measure, or clustered bar chart.
A single-measure bar chart shows one measure for one dimension, for example average delay time by flight number.
A multi-measure bar chart shows two or more measures for one dimension, for example sales total and profit total by automobile mode.
A clustered bar chart shows values for a dimension grouped by a related dimension, for example sales totals by automobile model, grouped by car maker.
https://docs.aws.amazon.com/quicksight/latest/user/bar-charts.htmlOption B is correct - On the clustered bar combo chart, bars display for each child dimension, grouped by the parent dimension.
On the stacked bar combo chart, one bar displays per parent dimension.
https://docs.aws.amazon.com/quicksight/latest/user/bar-charts.html https://docs.aws.amazon.com/quicksight/latest/user/bar-charts.htmlOption C is incorrect - heat maps to show a measure for the intersection of two dimensions, with color-coding to easily differentiate where values fall in the range.
https://docs.aws.amazon.com/quicksight/latest/user/heat-map.htmlOption D is incorrect - Use line charts to compare changes in measure values over period of time.
One measure over a period of time, for example gross sales by month.
Multiple measures over a period of time, for example gross sales and net sales by month.
One measure for a dimension over a period of time, for example number of flight delays per day by airline.
https://docs.aws.amazon.com/quicksight/latest/user/line-charts.htmlThe team can achieve building charts on a single dimension, grouped dimensions against a single measure, and multiple measures and their aggregations and summaries based on X and Y dimensions using the following two options:
A. Bar Charts: Bar charts are useful when comparing values of a single dimension or group of dimensions against a single measure. MSP Bank's team can use bar charts to display the data in a vertical or horizontal bar format. For example, if they want to display the sales revenue of different products in a particular quarter, they can use a bar chart to compare the revenue of each product.
B. Combo Charts: Combo charts combine two or more chart types on the same axis. MSP Bank's team can use combo charts to display multiple measures and their aggregations and summaries based on X and Y dimensions. For example, they can display the sales revenue of different products and the number of units sold for each product in a single chart. Combo charts provide a comprehensive view of the data and make it easy to identify patterns and trends.
C. Heat Maps: Heat maps are useful for visualizing data in two dimensions, where the values are represented by colors. Heat maps are useful when the team needs to display large amounts of data and identify patterns in the data quickly. However, heat maps are not useful when comparing data across multiple dimensions.
D. Line Charts: Line charts are useful for displaying data over time or continuous data points. MSP Bank's team can use line charts to display trends and patterns over time or continuous data points. Line charts are not useful for comparing data across multiple dimensions.
In summary, the team can achieve building charts on a single dimension, grouped dimensions against a single measure, and multiple measures and their aggregations and summaries based on X and Y dimensions using Bar charts and Combo charts.