A new field calculated at run time

A fascinating topic!

In data analysis and science, a new field calculated at runtime is often referred to as a "derived field" or "calculated column". It's a column or field that is generated on the fly, based on the values in other columns or fields, during the execution of a query or analysis.

Here are some examples of new fields calculated at runtime:

  1. Aggregations: Calculating the sum, average, or count of values in a column, such as SUM(sales) or AVG(age).
  2. Derived metrics: Creating new metrics by combining existing ones, such as conversion_rate = (conversions / impressions) * 100.
  3. Transformations: Applying transformations to existing data, such as converting dates to a specific format or normalizing numerical values.
  4. Joining data: Combining data from multiple tables or datasets to create a new field, such as customer_name = customer_table.name.
  5. Machine learning models: Training machine learning models on the fly to generate predictions or classifications, such as predicted_sales = linear_regression_model.predict(sales_data).

New fields calculated at runtime can be useful in various scenarios:

  1. Data exploration: Quickly generating new insights or visualizations to understand the data.
  2. Data preparation: Transforming data to make it suitable for analysis or modeling.
  3. Real-time analytics: Generating insights or predictions in real-time, such as tracking website traffic or monitoring stock prices.
  4. Machine learning: Training models on the fly to make predictions or classifications.

Some popular tools and technologies for calculating new fields at runtime include:

  1. Data manipulation libraries: Pandas (Python), NumPy (Python), and DataFrames (R).
  2. Data visualization tools: Tableau, Power BI, and D3.js.
  3. Machine learning frameworks: scikit-learn (Python), TensorFlow (Python), and PyTorch (Python).
  4. Database management systems: SQL databases like MySQL, PostgreSQL, and Oracle, as well as NoSQL databases like MongoDB and Cassandra.