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The Microsoft Azure Data Fundamentals exam covers various concepts related to data storage, processing, and visualization in the Azure ecosystem. When working with data, it is crucial to select appropriate visualizations to effectively communicate insights and patterns. In this article, we will explore different visualization techniques that can be employed in the context of Azure Data Fundamentals.
Bar charts are widely used to compare categories or data points. They consist of rectangular bars whose lengths are proportional to the values they represent. Bar charts are suitable for visualizing discrete data, such as counts or categorical variables. For example, you can use a bar chart to compare the number of records or transactions across different Azure storage accounts.
const canvas = document.getElementById('barChart');
const ctx = canvas.getContext('2d');
// Data to be displayed
const data = [10, 20, 30, 40, 50];
const labels = ['Category 1', 'Category 2', 'Category 3', 'Category 4', 'Category 5'];
// Bar colors
const colors = ['red', 'blue', 'green', 'yellow', 'orange'];
const barWidth = 40;
const maxValue = Math.max(...data);
// Draw bars
data.forEach((value, index) => {
const barHeight = (value / maxValue) * canvas.height;
ctx.fillStyle = colors[index];
ctx.fillRect(index * barWidth, canvas.height - barHeight, barWidth, barHeight);
});
// Draw labels
ctx.fillStyle = 'black';
ctx.font = '12px Arial';
labels.forEach((label, index) => {
ctx.fillText(label, index * barWidth, canvas.height - 5);
});
Line charts are used to visualize trends or patterns over a continuous range. They are particularly useful for showing changes in data over time. In Azure Data Fundamentals, a line chart can be employed to represent the growth or decline of storage usage over a period.
const canvas = document.getElementById('lineChart');
const ctx = canvas.getContext('2d');
// Data to be displayed
const data = [10, 20, 30, 40, 50];
const labels = ['January', 'February', 'March', 'April', 'May'];
// Line color
const color = 'blue';
ctx.strokeStyle = color;
ctx.lineWidth = 2;
const startY = canvas.height;
const maxValue = Math.max(...data);
// Draw line
ctx.beginPath();
ctx.moveTo(0, startY);
data.forEach((value, index) => {
const x = (index / (data.length - 1)) * canvas.width;
const y = canvas.height - (value / maxValue) * canvas.height;
ctx.lineTo(x, y);
});
ctx.stroke();
// Draw labels
ctx.fillStyle = 'black';
ctx.font = '12px Arial';
labels.forEach((label, index) => {
const x = (index / (labels.length - 1)) * canvas.width;
ctx.fillText(label, x, canvas.height - 5);
});
Pie charts are used to represent proportions or percentages of a whole. They are suitable for displaying data distributions. In Azure Data Fundamentals, a pie chart can be used to illustrate the composition of different data sources or storage types.
const canvas = document.getElementById('pieChart');
const ctx = canvas.getContext('2d');
// Data to be displayed
const data = [10, 20, 30, 40, 50];
const labels = ['Category 1', 'Category 2', 'Category 3', 'Category 4', 'Category 5'];
// Colors for pie slices
const colors = ['red', 'blue', 'green', 'yellow', 'orange'];
const centerX = canvas.width / 2;
const centerY = canvas.height / 2;
const radius = Math.min(canvas.width, canvas.height) / 2 - 10;
const total = data.reduce((sum, value) => sum + value, 0);
let startAngle = 0;
data.forEach((value, index) => {
const sliceAngle = (value / total) * 2 * Math.PI;
const endAngle = startAngle + sliceAngle;
// Draw slice
ctx.fillStyle = colors[index];
ctx.beginPath();
ctx.moveTo(centerX, centerY);
ctx.arc(centerX, centerY, radius, startAngle, endAngle);
ctx.closePath();
ctx.fill();
// Update start angle for the next slice
startAngle = endAngle;
});
// Draw labels and legends
ctx.fillStyle = 'black';
ctx.font = '12px Arial';
let legendX = 20;
labels.forEach((label, index) => {
ctx.fillStyle = colors[index];
ctx.fillRect(legendX, canvas.height - 18, 12, 12);
ctx.fillStyle = 'black';
ctx.fillText(label, legendX + 18, canvas.height - 8);
legendX += 120;
});
It is essential to select visualizations that effectively convey information and are appropriate for the type of data being analyzed. By using techniques like bar charts, line charts, and pie charts in the context of Azure Data Fundamentals, you can visually represent and explore data patterns efficiently. Remember to consider the specific requirements of your data and the insights you want to communicate when selecting the appropriate visualization technique.
Correct answer: c) Bar chart
Correct answer: b) Area chart
Correct answer: d) Box plot
Correct answer: b) Scatter plot
Correct answer: b) Tree map
Correct answer: a) Funnel chart
Correct answer: b) Choropleth map
Correct answer: d) Scatter plot
Correct answer: c) Pie chart
Correct answer: b) Bubble chart
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