1. Why Importing Data Matters

After identifying and preparing internal and external data, data analysts must import data into tools where analysis can happen. Spreadsheets are commonly used for this purpose because they are flexible, accessible, and easy to work with.

Importing data correctly ensures that:

  • Data structure is preserved
  • Fields and records are clearly separated
  • Analysis can begin without unnecessary rework

2. CSV Files (Comma-Separated Values)

A CSV file is one of the most common formats used to move data between systems.

Key characteristics of CSV files

  • Stores data in a table-like structure
  • Uses plain text
  • Separates values using delimiters (usually commas)
  • Compatible with most spreadsheet and database tools

Because of this simplicity, CSV files are widely used for data exchange.

3. Importing a CSV File into a Spreadsheet

A typical CSV import process includes the following steps:

Basic import steps

  • Open a new or existing spreadsheet
  • Select File → Import
  • Choose Upload and select the CSV file
  • Insert the file as a new sheet
  • Confirm import settings
  • Select Import data

Once imported, the dataset is ready for exploration and analysis.

4. Delimiters and Import Options

CSV files rely on delimiters to separate fields.

Common delimiters

  • Commas (most common)
  • Tabs
  • Spaces
  • Other special characters

Spreadsheet tools often auto-detect delimiters, but analysts may need to:

  • Manually specify the delimiter
  • Adjust data type conversions

For reporting or initial review, importing data as plain text is often sufficient.

5. Working with Subsets of Large Datasets

Analysts frequently begin with large datasets and extract smaller subsets into spreadsheets for focused analysis.

Example use cases

  • Analyzing year-over-year demand trends
  • Comparing usage across regions or time periods
  • Reviewing selected variables from a larger database

This approach improves efficiency and clarity.

6. Using External Open Data Sources

Many organizations provide open-source datasets that analysts can download and analyze.

Example: World Health Organization (WHO)

The WHO data repository provides:

  • Open-access datasets
  • Filters by theme, category, indicator, and country
  • Metadata describing how data was collected

Example dataset

  • Number of medical doctors by country and year

This data can support analyses such as:

  • Comparing healthcare capacity across populations
  • Evaluating doctor availability relative to population size

7. Importing External Data into a Spreadsheet

The process for importing external data is similar to importing internal data.

Typical workflow

  • Locate the dataset on the source website
  • Download the file as a CSV
  • Open a new spreadsheet
  • Select File → Import
  • Upload and import the data
  • Review for structure and cleanliness
  • Add a clear title to the dataset

After import, the data is ready for analysis.

8. Key Takeaways

  • Importing data is a core data analysis skill
  • CSV files are a common and flexible data format
  • Delimiters define how fields are separated
  • Spreadsheet tools usually auto-detect delimiters
  • Large datasets are often analyzed using smaller subsets
  • Open data repositories provide valuable external data
  • Reviewing imported data ensures accuracy and readiness

One-sentence summary

Importing CSV and external datasets into spreadsheets allows data analysts to transform raw data into an accessible format for efficient exploration and analysis.