Heading Hierarchy

Heading 2

Heading 3

Heading 4

Heading 5

Heading 6

A well-designed article should have a clear visual hierarchy.

The h1 normally represents the article title, while h2 and h3 divide the article into logical sections.

Text Formatting

This is bold text.

This is italic text.

This is bold and italic text.

This is deleted text.

This is underlined text.

This is highlighted text.

This is small text.

This is H₂O.

This is X².

This is inline code.

This is Ctrl + C.

You can also use KPI abbreviations.

Here is a link GitHub that opens in the same tab. And GitHub will open in a new tab.

Images

Blockquotes

Data is valuable only when it helps someone make a better decision.

A longer blockquote can contain multiple paragraphs.

Analysis requires curiosity.

Visualization requires clarity.

Communication requires understanding your audience.

Nested Blockquotes

This is the first level.

This is the second level.

This is the third level.

Unordered Lists

• Sales
  • Revenue
  • Units
  • Orders
• Customers
  • New customers
  • Returning customers
• Products
  • Best sellers
  • Worst sellers

Ordered Lists

1. Data preparation
   1. Remove duplicates
   2. Handle missing values
   3. Standardize formats
2. Analysis
   1. Calculate KPIs
   2. Compare periods
   3. Identify anomalies
3. Reporting
   1. Build dashboard
   2. Present insights
   3. Recommend action

Task Lists

• Collect data
• Clean data
• Build data model
• Create measures
• Validate results
• Present findings

Definition List

Revenue

The total income generated from selling products or services.

Profit

The amount remaining after subtracting costs from revenue.

Margin

Profit expressed as a percentage of revenue.

KPI

A measurable value used to evaluate performance against a business objective.

Code

A simple Python calculation:

revenue = 275
quantity = 65

average_revenue = revenue / quantity

print(average_revenue)

SQL Example

SELECT
    category,
    SUM(revenue) AS total_revenue,
    SUM(quantity) AS units_sold
FROM sales
GROUP BY category
ORDER BY total_revenue DESC;

DAX Example

Total Revenue =
SUM ( Sales[Revenue] )

Power Query Example

let
    Source = Excel.CurrentWorkbook(){[Name="Sales"]}[Content],
    ChangedType = Table.TransformColumnTypes(
        Source,
        {
            {"Revenue", type number},
            {"Quantity", Int64.Type}
        }
    )
in
    ChangedType

When writing SQL, the SUM() function can be used to calculate totals.

Mathematical Expressions

1. Global Sets & Custom Macros

• Inline Sets: Let $x \in \R$, $y \in \C$, $z \in \Z$, and $n \in \N$.
• Vector Sum Macro (\vectorsum{n}): \(\vectorsum{5} = \vec{v}_1 + \vec{v}_2 + \vec{v}_3 + \vec{v}_4 + \vec{v}_5\)
• Highlight Macro (\highlight{math}): \(\highlight{\int_{0}^{\infty} e^{-x^2} dx = \frac{\sqrt{\pi}}{2}}\)

2. Physics & Quantum Mechanics (physics)

• Partial Derivatives: $\pdv{f}{x}$ and mixed second derivatives: \(\pdv[2]{f}{x}{y} = \pdv{}{x}\left(\pdv{f}{y}\right)\)
• Schrödinger Equation with Bra-Ket Notation: \(i\hbar \pdv{\Psi}{t} = \hat{H}\Psi \implies \mel{\psi_a}{\hat{H}}{\psi_b} = E_a \braket{\psi_a}{\psi_b}\)

3. Chemistry Equations (mhchem)

• Precipitation Equilibrium: \(\ce{Ag+(aq) + Cl-(aq) <=> AgCl(v)}\)
• Thermochemical Reaction with Conditions: \(\ce{2H2(g) + O2(g) ->[{Pt\text{ catalyst}}][{\Delta}] 2H2O(l)} \quad \Delta H = -571.6\text{ kJ}\)

4. Advanced Colors & Canceling (color / xcolor & cancel)

• Color Mixing & Hex Codes: \(\textcolor{blue!60!red}{\text{60\% Blue + 40\% Red}} \quad \text{and} \quad \textcolor{#ff5733}{\text{Hex Color \#FF5733}}\)
• Canceling Terms in Algebraic Simplification: \(\frac{(x - 1)(x + 3)\cancel{(2x + 5)}}{\xcancel{(2x + 5)}\bcancel{(x - 1)}} = x + 3\)

5. Alignment, Numbering & Extensible Arrows (mathtools & AMS)

• Numbered align Environment with Extensible Arrows: \(\begin{align} A &\xRightarrow[\text{decomposition}]{\text{heat}} \textcolor{red}{\ce{2NaNO3}} + \ce{O2} \\ B &\xrightarrow[k_{-1}]{k_1} \highlight{\sum_{i=1}^{n} X_i^2} \in \R \end{align}\)

Horizontal Rule

The horizontal rule below should be visually distinct.

Table

Video

Audio

Details and Summary

Footnotes

Data visualization is an important part of analytical communication.¹

A KPI should always be evaluated against an appropriate benchmark.²

Long-Form Paragraph

A professional analytical report should provide enough context for the reader to understand not only what happened but also why it happened and what should happen next. This means that the analyst needs to understand the business process behind the data. A beautifully designed dashboard can still fail if it presents irrelevant metrics, uses misleading comparisons, or forces stakeholders to perform the interpretation themselves. Good analytical communication therefore combines accurate calculations, appropriate visualizations, concise explanations, and actionable recommendations. The objective is not to overwhelm the reader with information but to make the important information easier to find and understand.