Skip to main content

Common Data Terms

Definitions of common data terms, acronyms, and how you may see them in data visualization. 

Data Descriptions

These terms are often used to describe data in visualizations – be it a word cloud, bar chart, big aggregate number (BAN), or on an axis. 

  • Aggregation
    • What it means: a summarized view of the data. By default, Tableau is set to aggregate data. 
    • How you may see it: Any large numbers, such as number of students enrolled, outstanding PCards, or dollars raised are aggregates. 
  • Axis
    • What it means: Axes provide vital reference information for users to associate data points with values – especially when data points are not labeled directly in a chart. Charts may contain two axes: an x-axis and a y-axis. 
      • X-axis: the x-axis is a horizontal line 
      • Y-axis: the y-axis is a vertical line. 
      • An easy way to remember the two is “x to the left and y to the sky”. 
    • How you may see it: Quantitative or numeric data, such as bar charts, frequently use axes. 
  • Count
    • What it means: the total number of items. For example, if given 1, 2, 3, 3, there is a count of 4. 
    • Acronyms: CNT
  • Count Distinct
    • What it means: the total unique number of items. For example, if given 1, 2, 3, 3 there is a distinct count of 3 – as there are only 3 unique values. 
    • Acronyms: CNTD, Count Distinct, Unique Count, Distinct Count
    • Count and Count Distinct in data visualization may be labeled on the axis or when you see a large, aggregate number on a dashboard. 
  • Legend
    • What it means: A legend, or a key, is used to identify data by color, size, shape, or other distinguishing features. 
    • How you may see it: Legends may be a small area outside of the chart or it could be a combination of words and colors. For example, if blue represents the prior year, then a legend may say Prior Year. 
  • Minimum
    • What it means: the lowest value in a data set. For example, if my data set is 1, 2, 3, the minimum is 1 (the lowest value). 
    • Acronyms: MIN
  • Maximum
    • What it means: the largest value in a data set. For example, if my data set is 1, 2, 3 the maximum is 3 (the highest value). 
    • Acronyms: MAX
  • Qualitative Data
    • What it means: Qualitative data is descriptive or non-numerical (think of words). It can be collected through surveys, interviews, or focus groups. 
    • How you may see it: word clouds
  • Quantitative Data
    • What it means: Quantitative data is numeric and objective. 
    • How you may see it: line graphs, maps, or scatter plots. 

Functionality

The terms below are used by analysts in units to describe functionality within a visualization tool. 

  • Data Source
    • What it means: A data source is the origin of a set of information. It can be a location, systems, database, document, flat file, or any other readable digital format. 
    • Acronyms: TDS (Tableau data source)
    • How you may see it in data visualization: All reports in Tableau have a data source. It may update on a schedule or be a live connection (meaning it’s as updated as the source). 
  • ETL
    • What it means: ETL is a common acronym for Extract, Transform, and Load. ETL tools collect and process data from various sources into a single data store making it much easier to analyze. 
    • How you may see it in data visualization: Tableau Prep is a free ETL tool, with a Tableau Desktop license. Analysts may use it if a lot of calculations are required for the report or the data is stored in several different places. Tableau Prep creates and streamlines data sources for reports. 
  • Lineage
    • What it means: tells you were the data originated. It’s the process of understanding, recording, and visualizing data as it flows from origin to destination. 
    • How you may see it in a data visualization: Lineage is a tab on all workbook urls; it allows users the ability to visualize and interact with data from the origin to the destination. It feeds into the data catalog and data guide. 
    • How it can be used:
      • Share who is using a data source to build a dashboard
      • Identify impacted assets if there is a change in business logic
  • Metadata
    • What it means: data that describes and provides information about other data
    • How you may see it in data visualization: if the workbook has a description (such as purpose or intended audience), this is metadata. Metadata is crucial for helping users find the right information and feeds into the university’s data catalog.