Billing dashboard overview in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ dax_lod_result

intermediate

Calculate Total Monthly Cost Using DAX

You have a billing dataset with columns: Date, Service, and Cost. Which DAX measure correctly calculates the total cost for the current month?

A Total Monthly Cost = CALCULATE(SUM(Billing[Cost]), FILTER(Billing, MONTH(Billing[Date]) = MONTH(TODAY()) && YEAR(Billing[Date]) = YEAR(TODAY())))

B Total Monthly Cost = SUMX(FILTER(Billing, Billing[Date] = TODAY()), Billing[Cost])

C Total Monthly Cost = CALCULATE(SUM(Billing[Cost]), ALL(Billing))

D Total Monthly Cost = SUM(Billing[Cost])

💡 Hint

Use CALCULATE with FILTER to restrict data to current month and year.

Option A correctly filters the billing data to only include rows where the date is in the current month and year, then sums the Cost.

Option A sums all costs without filtering by date.

Option A removes filters and sums all costs, ignoring date.

Option A filters only for today's date, not the whole month.

❓ visualization

intermediate

Best Visualization for Cost Trend Over Time

You want to show how AWS billing costs change month by month over the past year. Which visualization type is best suited for this?

A Bar chart showing total cost by service for the current month

B Pie chart showing cost distribution by service

C Line chart showing monthly total cost over time

D Scatter plot showing cost vs. number of resources

💡 Hint

Think about how to show changes over time clearly.

A line chart is ideal for showing trends over time, such as monthly billing costs.

Pie charts show parts of a whole at one point in time, not trends.

Bar charts can compare categories but are less effective for continuous time trends.

Scatter plots show relationships between two variables, not time trends.

❓ data_modeling

advanced

Designing a Data Model for Billing Analysis

You have raw AWS billing data with many services and usage types. To build an efficient billing dashboard, which data modeling approach is best?

A Store all raw data in a single flat table without relationships

B Create a star schema with a fact table for usage and dimension tables for services, dates, and accounts

C Use multiple unrelated tables for each service without common keys

D Create a snowflake schema with many normalized dimension tables but no fact table

💡 Hint

Think about how to organize data for fast queries and easy filtering.

A star schema with a fact table and dimension tables is best for BI dashboards because it supports efficient queries and clear relationships.

Option B leads to slow queries and difficulty filtering.

Option B lacks relationships, making analysis hard.

Option B is overly complex and less performant for typical BI needs.

🔧 Debug

advanced

Identify the Error in This DAX Measure

This DAX measure is intended to calculate the average daily cost for the current month but returns an error. What is the cause?

AWS

Avg Daily Cost = AVERAGEX(FILTER(Billing, MONTH(Billing[Date]) = MONTH(TODAY())), Billing[Cost])

A Billing[Cost] cannot be used inside AVERAGEX without aggregation

B AVERAGEX requires a table as the first argument, but FILTER returns a scalar

C TODAY() cannot be used inside FILTER

D The FILTER function is missing a YEAR condition, causing incorrect filtering

💡 Hint

Check if the filter includes the correct year to avoid mixing months from different years.

The measure filters only by month but not by year, so it mixes data from the same month in all years, causing wrong results or errors.

FILTER returns a table, so AVERAGEX works correctly.

Billing[Cost] is valid inside AVERAGEX.

TODAY() can be used inside FILTER.

🧠 Conceptual

expert

Scenario: Optimizing Billing Dashboard Performance

Your billing dashboard is slow because it queries a very large dataset live. Which approach will best improve performance without losing data accuracy?

A Implement incremental data refresh to load only new billing data daily and pre-aggregate monthly costs

B Use direct query mode to always get the latest data without caching

C Remove all filters and show raw data to speed up queries

D Split the dataset into many small unrelated tables to reduce size

💡 Hint

Think about balancing data freshness and query speed with pre-processing.

Incremental refresh loads only new data and pre-aggregations reduce query complexity, improving performance while keeping accuracy.

Removing filters shows too much data and slows queries.

Direct query mode can be slower on large datasets.

Splitting tables without relationships complicates analysis and may not improve speed.

Practice

1. What is the main purpose of an AWS billing dashboard?

easy

A. To write code for AWS Lambda functions

B. To create new AWS resources automatically

C. To monitor server uptime and performance

D. To show your cloud costs clearly and help manage your budget

Solution

1. Step 1: Understand the billing dashboard function

   The billing dashboard is designed to display cloud costs and usage clearly.

2. Step 2: Identify the correct purpose

   It helps users track spending and manage budgets, not resource creation or monitoring uptime.

3. Final Answer:

   To show your cloud costs clearly and help manage your budget -> Option D

4. Quick Check:

   Billing dashboard = cost visibility [OK]

Hint: Billing dashboard = clear cost view [OK]

Common Mistakes:

• Confusing billing dashboard with resource management
• Thinking it monitors server performance
• Assuming it automates AWS resource creation

2. Which AWS service provides the billing dashboard to track your cloud costs?

easy

A. AWS Cost Explorer

B. AWS CloudTrail

C. AWS Lambda

D. Amazon S3

Solution

1. Step 1: Identify AWS services related to billing

   AWS Cost Explorer is the service designed for cost tracking and billing dashboards.

2. Step 2: Eliminate unrelated services

   CloudTrail tracks API calls, Lambda runs code, and S3 stores data, so they don't provide billing dashboards.

3. Final Answer:

   AWS Cost Explorer -> Option A

4. Quick Check:

   Cost Explorer = billing dashboard tool [OK]

Hint: Cost Explorer shows billing info clearly [OK]

Common Mistakes:

• Choosing CloudTrail which tracks logs, not costs
• Confusing Lambda with billing tools
• Selecting S3 which is for storage only

3. You create a billing dashboard with a line chart showing monthly AWS costs. If your costs were $100 in January, $150 in February, and $120 in March, what trend does the chart show?

medium

A. Costs decreased every month

B. Costs are steadily increasing every month

C. Costs increased from January to February, then decreased in March

D. Costs stayed the same each month

Solution

1. Step 1: Analyze the monthly cost values

   January = $100, February = $150, March = $120 shows an increase then a decrease.

2. Step 2: Interpret the trend on the line chart

   The line rises from January to February, then falls from February to March.

3. Final Answer:

   Costs increased from January to February, then decreased in March -> Option C

4. Quick Check:

   100 -> 150 ↑, then 150 -> 120 ↓ [OK]

Hint: Look for rises and falls in monthly values [OK]

Common Mistakes:

• Assuming costs always increase
• Ignoring the drop in March
• Thinking costs stayed constant

4. You set up a billing dashboard but notice the monthly cost chart shows zero for all months. What is the most likely cause?

medium

A. Your AWS account has no active resources

B. You forgot to enable cost data collection in AWS Cost Explorer

C. The chart type is set to pie instead of line

D. You used the wrong AWS region in the dashboard

Solution

1. Step 1: Check data collection settings

   If cost data collection is not enabled, the dashboard will show zero costs.

2. Step 2: Consider other causes

   While no active resources or wrong region might affect data, the most common cause is missing cost data collection.

3. Final Answer:

   You forgot to enable cost data collection in AWS Cost Explorer -> Option B

4. Quick Check:

   Enable cost data collection to see costs [OK]

Hint: Enable cost data collection first [OK]

Common Mistakes:

• Assuming no resources means zero costs always
• Changing chart type without checking data
• Ignoring cost data collection settings

5. You want to create a billing dashboard that shows daily AWS costs for the last 30 days and highlights days when costs exceed $200. Which AWS feature combination should you use?

hard

A. AWS Cost Explorer with custom filters and a conditional formatting table

B. AWS CloudWatch to monitor costs and AWS Lambda to send alerts

C. Amazon S3 to store cost data and Amazon QuickSight for visualization

D. AWS IAM to restrict access and AWS Budgets to set alerts

Solution

1. Step 1: Identify tools for cost visualization and filtering

   AWS Cost Explorer allows creating custom filters and visualizations for daily costs.

2. Step 2: Use conditional formatting to highlight costs over $200

   Cost Explorer supports tables with conditional formatting to highlight high costs.

3. Final Answer:

   AWS Cost Explorer with custom filters and a conditional formatting table -> Option A

4. Quick Check:

   Cost Explorer + filters + formatting = daily cost highlights [OK]

Hint: Use Cost Explorer filters and formatting for highlights [OK]

Common Mistakes:

• Using CloudWatch which is for performance, not billing visualization
• Choosing S3 without visualization tools
• Confusing IAM and Budgets with visualization features