Data Formats and Types: An Overview

When you think about the word "format," a lot of things might come to mind. Think of an advertisement for your favorite store. You might find it in the form of a print ad, a billboard, or even a commercial. The information is presented in the format that works best for you to take it in. The format of a dataset is a lot like that, and choosing the right format will help you manage and use your data in the best way possible.

Data format examples

Primary Data Vs Secondary Data:

• Primary Data:

                         Collected by a researcher from a first hand source.

                                        eg: Data from an interview you conducted

• Secondary Data:

Gathered by other people or from other researchers.

                                        eg: Data you bought from a local data analytics firm’s customer profiles

Internal Data Vs External Data:

• Internal Data:

  Data that lives within the company's own system.

eg: Wages of employees across different business units tracked by HR

Sales data by store location

Product inventory levels across distribution centers

• External Data:

                          Data that lives or collected from outside the organisation.

                                        eg: National average wages for the various positions throughout your organisation

Continuous Data Vs Discrete Data:

• Continuous Data:

                           Data that is measured and can have almost any numeric value.

eg: Height of kids in third grade classes (52.5 inches, 65.7 inches)

• Discrete Data:

                          Data that can be counted and should have countable number of values.

                                   eg: Number of people who visit a hospital on a daily basis (10, 20, 200)

Structured Data Vs Unstructured Data:

• Structured Data:

  Data organised in certain format like rows and columns.

eg: Expense reports

• Unstructured Data:

Data that isn’t organized in any easily identifiable manner.

eg: Social media posts

Nominal Data Vs Ordinal Data:

• Nominal Data:

                           A type of qualitative data that isn’t categorized with a set order.

eg: First time customer, returning customer, regular customer

• Ordinal Data:

   A type of qualitative data with a set order or scale.

eg: Movie ratings (number of stars: 1 star, 2 stars, 3 stars)

Qualitative Data Vs Quantitative Data:

• Qualitative Data:

  Subjective and explanatory measures of qualities and characteristics.

eg: Favorite brands of most loyal customers

• Quantitative Data:

  Specific and objective measures of numerical facts.

eg: Percentage of board certified doctors who are women