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Shashank Trivedi
Shashank Trivedi

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Key terms In data analytics

You must have heard about the terms Metric , What is a Dimension , what is a segment and even what is a characteristic , how these terms are different and why it is important to understand each of them.

Let's begin.

Metric: A measurable number that quantifies performance or an outcome.A metric is a numerical value that represents something you’re tracking.
Examples:

  • Website analytics: Page views, Sessions, Bounce rate.
  • E-commerce: Revenue, Total orders, Conversion rate.

Dimensions: A descriptive attribute that adds context to a metric.A dimension gives more context to your data, often answering "when," "where," or "which category.

For a metric like Total sales:
- Dimensions could be:
- Date (Sales on Oct 17)
- Product category (Shoes vs. Electronics)
- Location (Sales from New York)

Characteristics: Qualities or features of the data or dataset that describe how it behaves.Characteristics describe patterns or behaviors of the data.
A characteristic of website traffic might be:
- High bounce rate in certain countries.
- Seasonal behavior (more traffic during holidays).

Segment:A segment is a subset of data that shares common attributes based on specific conditions. Focused part of your data.
Example : slice of a pizza. ,High-value customer, Abandoned cart users

Bringing it all together with an Example
Imagine you run an online shoe store.

  • Metric: You measure Revenue (numerical).
  • Dimension: You break revenue down by Product category (e.g., sports shoes, formal shoes).
  • Characteristic: You notice seasonality—higher revenue in December due to holiday shopping.

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