Glossary
Terms and Definitions
A/B testing: The process of testing two variations of the same web page to determine which page is more successful at attracting user traffic and generating revenue
Absolute reference: A reference within a function that is locked so that rows and columns won’t change if the function is copied
Access control: Features such as password protection, user permissions, and encryption that are used to protect a spreadsheet
Accuracy: The degree to which data conforms to the actual entity being measured or described
Action-oriented question: A question whose answers lead to change
Administrative metadata: Metadata that indicates the technical source of a digital asset
Aesthetic (R): A visual property of an object in a plot
Agenda: A list of scheduled appointments
Aggregation: The process of collecting or gathering many separate pieces into a whole
Algorithm: A process or set of rules followed for a specific task
Aliasing: Temporarily naming a table or column in a query to make it easier to read and write
Alternative text: Text that provides an alternative to non-text content, such as images and videos
Analytical skills: Qualities and characteristics associated with using facts to solve problems
Analytical thinking: The process of identifying and defining a problem, then solving it by using data in an organized, step-by-step manner
Annotation: Text that briefly explains data or helps focus the audience on a particular aspect of the data in a visualization
Anscombe’s quartet: Four datasets that have nearly identical summary statistics but contain different plotted values
Area chart: A data visualization that uses individual data points for a changing variable connected by a continuous line with a filled in area underneath
Argument (R): Information needed by a function in R in order to run
Arithmetic operator: An operator used to perform basic math operations such as addition, subtraction, multiplication, and division
Array: A collection of values in spreadsheet cells
Assignment operator: An operator used to assign values to variables and vectors
Attribute: A characteristic or quality of data used to label a column in a table
Audio file: Digitized audio storage usually in an MP3, AAC, or other compressed format
AVERAGE: A spreadsheet function that returns an average of the values from a selected range
AVERAGEIF: A spreadsheet function that returns the average of all cell values from a given range that meet a specified condition
Bad data source: A data source that is not reliable, original, comprehensive, current, and cited (ROCCC)
Balance: The design principle of creating aesthetic appeal and clarity in a data visualization by evenly distributing visual elements
Bar graph: A data visualization that uses size to contrast and compare two or more values
Bias: A conscious or subconscious preference in favor of or against a person, group of people, or thing
Big data: Large, complex datasets typically involving long periods of time, which enable data analysts to address far-reaching business problems
Boolean data: A data type with only two possible values, usually true or false
Borders: Lines that can be added around two or more cells on a spreadsheet
Box plot: A data visualization that displays the distribution of values along an x-axis
Bubble chart: A data visualization that displays individual data points as bubbles, comparing numeric values by their relative size
Bullet graph: A data visualization that displays data as a horizontal bar chart moving toward a desired value
Business metric: A standard of measurement used to solve a business task
Business task: The question or problem data analysis resolves for a business
C# : An object-oriented programming language used to create games and mobile apps in the .NET open source developer platform
C++: An extension of the C programming language that is used to create console games, such as those for Xbox
Calculated field: A new field within a pivot table that carries out certain calculations based on the values of other fields
Calculus: A branch of mathematics that involves the study of rates of change and the changes between values that are related by a function
CASE: A SQL statement that returns records that meet conditions by including an if/then statement in a query
Case study: A common way for employers to assess job skills and gain insight into how a candidate approaches common data-related challenges
CAST: A SQL function that converts data from one datatype to another
Causation: When an action directly leads to an outcome, such as a cause-effect relationship
Cell reference: A cell or a range of cells in a worksheet typically used in formulas and functions
Changelog: A file containing a chronologically ordered list of modifications made to a project
Channel: A visual aspect or variable that represents characteristics of the data in a visualization
Chart: A graphical representation of data from a worksheet
Circle view: A data visualization that shows comparative strength in data
Clean data: Data that is complete, correct, and relevant to the problem being solved
Cloud: A place to keep data online, rather than a computer hard drive
Cluster: A collection of data points on a data visualization with similar values
COALESCE: A SQL function that returns non-null values in a list
Code chunk: A piece of code added in an R Markdown file that is used to process, visualize or analyze data
Coding: The process of writing instructions to a computer in the syntax of a specific programming language
Column chart: A data visualization that uses individual data points for a changing variable, represented as vertical columns
Combo chart: A data visualization that combines more than one visualization type
Compatibility: How well two or more datasets are able to work together
Completeness: The degree to which data contains all desired components or measures
Computer programming: The process of giving instructions to a computer in order to perform an action or set of actions
CONCAT: A SQL function that adds strings together to create new text strings that can be used as unique keys
CONCATENATE: A spreadsheet function that joins together two or more text strings
Conditional formatting: A spreadsheet tool that changes how cells appear when values meet specific conditions
Conditional statement: A declaration that if a certain condition holds, then a certain event must take place
Confidence interval: A range of values that conveys how likely a statistical estimate reflects the population
Confidence level: The probability that a sample size accurately reflects the greater population
Confirmation bias: The tendency to search for or interpret information in a way that confirms pre-existing beliefs
Consent: The aspect of data ethics that presumes an individual’s right to know how and why their personal data will be used before agreeing to provide it
Consistency: The degree to which data is repeatable from different points of entry or collection
Context: The condition in which something exists or happens
Continuous data: Data that is measured and can have almost any numeric value
CONVERT: A SQL function that changes the unit of measurement of a value in data
Cookie: A small file stored on a computer that contains information about its users
Correlation: The measure of the degree to which two variables change in relationship to each other
COUNT: A spreadsheet function that counts the number of cells within a range the meet a specified condition
COUNTA: A spreadsheet function that counts the total number of values within a specified range that meet specified criteria
COUNTIF: A spreadsheet function that returns the number of cells within a range that match a specified value
COUNT DISTINCT: A SQL function that only returns the distinct values in a specified range
CRAN (Comprehensive R Archive Network) (R): An online archive with R packages, source code, manuals, and documentation
CREATE TABLE: A SQL clause that adds a temporary table to a database that can be used by multiple people
Cross-field validation: A process that ensures certain conditions for multiple data fields are satisfied
CSS (Cascading Style Sheets): A programming language used for web page design that controls graphic elements and page presentation
CSV (comma-separated values) file: A delimited text file that uses a comma to separate values
Currency: The aspect of data ethics that presumes individuals should be aware of financial transactions resulting from the use of their personal data and the scale of those transactions
Dashboard: A tool that monitors live, incoming data
Data: A collection of facts
Data aggregation: The process of gathering data from multiple sources and combining it into a single, summarized collection
Data analysis: The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making
Data analysis process: The six phases of ask, prepare, process, analyze, share, and act whose purpose is to gain insights that drive informed decision-making
Data analyst: Someone who collects, transforms, and organizes data in order to draw conclusions, make predictions, and drive informed decision-making
Data analytics: The science of data
Data anonymization: The process of protecting people's private or sensitive data by eliminating identifying information
Data bias: When a preference in favor of or against a person, group of people, or thing systematically skews data analysis results in a certain direction
Data blending: A Tableau method that combines data from multiple data sources
Data composition: The process of combining the individual parts in a visualization and displaying them together as a whole
Data constraints: The criteria that determine whether a piece of a data is clean and valid
Data design: How information is organized
Data-driven decision-making: Using facts to guide business strategy
Data ecosystem: The various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data
Data element: A ****piece of information in a dataset
Data engineer: A professional who transforms data into a useful format for analysis and gives it a reliable infrastructure
Data ethics: Well-founded standards of right and wrong that dictate how data is collected, shared, and used
Data frame: A collection of columns containing data, similar to a spreadsheet or SQL table
Data governance: A process for ensuring the formal management of a company’s data assets
Data-inspired decision-making: Exploring different data sources to find out what they have in common
Data integrity: The accuracy, completeness, consistency, and trustworthiness of data throughout its life cycle
Data interoperability: The ability to integrate data from multiple sources and a key factor leading to the successful use of open data among companies and governments
Data life cycle: The sequence of stages that data experiences, which include plan, capture, manage, analyze, archive, and destroy
Data manipulation: The process of changing data to make it more organized and easier to read
Data mapping: The process of matching fields from one data source to another
Data merging: The process of combining two or more datasets into a single dataset
Data model: A tool for organizing data elements and how they relate to one another
Data privacy: Preserving a data subject’s information any time a data transaction occurs
Data range: Numerical values that fall between predefined maximum and minimum values
Data replication: The process of storing data in multiple locations
Data science: A field of study that uses raw data to create ****new ways of modeling and understanding the unknown
Data security: Protecting data from unauthorized access or corruption by adopting safety measures
Data storytelling: Communicating the meaning of a dataset with visuals and a narrative that are customized for an audience
Data strategy: The management of the people, processes, and tools used in data analysis
Data structure: A format for organizing and storing data
Data transfer: The process of copying data from a storage device to computer memory or from one computer to another
Data type: An attribute that describes a piece of data based on its values, its programming language, or the operations it can perform
Data validation: A tool for checking the accuracy and quality of data
Data validation process: The process of checking and rechecking the quality of data so that it is complete, accurate, secure and consistent
Data visualization: The graphical representation of data
Data warehousing specialist: A professional who develops processes and procedures to effectively store and organize data
Database: A collection of data stored in a computer system
Dataset: A collection of data that can be manipulated or analyzed as one unit
DATEDIF: A spreadsheet function that calculates the number of days, months, or years between two dates
Decision tree: A tool that helps analysts make decisions about critical features of a visualization
Delimiter: A character that indicates the beginning or end of a data item
Density map: A data visualization that represents concentrations, with color representing the number or frequency of data points in a given area on a map
Descriptive metadata: Metadata that describes a piece of data and can be used to identify it at a later point in time
Design thinking: A process used to solve complex problems in a user-centric way
Digital photo: An electronic or computer-based image usually in BMP or JPG format
Dirty data: Data that is incomplete, incorrect, or irrelevant to the problem to be solved
Discrete data: Data that is counted and has a limited number of values
DISTINCT: A keyword that is added to a SQL SELECT statement to retrieve only non-duplicate entries
Distribution graph: A data visualization that displays the frequency of various outcomes in a sample
Diverging color palette: A color theme that displays two ranges of data values using two different hues, with color intensity representing the magnitude of the values
Donut chart: A data visualization where segments of a ring represent data values adding up to a whole
dplyr (R): An R package in Tidyverse that offers a consistent set of functions to complete common data-manipulation tasks
DROP TABLE: A SQL clause that removes a temporary table from a database
Duplicate data: Any record that inadvertently shares data with another record
Dynamic visualizations: Data visualizations that are interactive or change over time
Elevator pitch: A short statement describing an idea or concept
Emphasis: The design principle of arranging visual elements to focus the audience’s attention on important information in a data visualization
Engagement: Capturing and holding someone’s interest and attention during a data presentation
Equation: A calculation that involves addition, subtraction, multiplication, or division (also called a math expression)
Estimated response rate: The average number of people who typically complete a survey
Ethics: Well-founded standards of right and wrong that prescribe what humans ought to do, usually in terms of rights, obligations, benefits to society, fairness, or specific virtues
External data: Data that lives, and is generated, outside of an organization
Facets (R): A series of functions that splits data into subsets in a matrix of panels
Factor (R): An object that stores categorical data where the data values are limited and usually based on a finite group, such as country or year
Fairness: A quality of data analysis that does not create or reinforce bias
Field: A single piece of information from a row or column of a spreadsheet; ****in a data table, typically a column in the table
Field length: A tool for determining how many characters can be keyed into a spreadsheet field
Fill handle: A box in the lower-right-hand corner of a selected spreadsheet cell that can be dragged through neighboring cells in order to continue an instruction
Filled map: A data visualization that colors areas in a map based on measurements or dimensions
Filtering: The process of showing only the data that meets a specified criteria while hiding the rest
Find and replace: A tool that finds a specified search term and replaces it with something else
First-party data: Data collected by an individual or group using their own resources
Float: A number that contains a decimal
Foreign key: A field within a database table that is a primary key in another table (Refer to primary key)
Formula: A set of instructions used to perform a calculation using the data in a spreadsheet
Framework: The context a presentation needs to create logical connections that tie back to the business task and metrics
FROM: The section of a query that indicates from which table(s) to extract the data
Function: A preset command that automatically performs a specific process or task using the data in a spreadsheet
Function (R): A body of reusable code for performing specific tasks in R
FWF (fixed-width file): A text file with a specific format, which enables the saving of textual data in an organized fashion
GAM (generalized additive model) smoothing (R): A process for smoothing plots with a large number of points
Gantt chart: A data visualization that displays the duration of events or activities on a timeline
Gap analysis: A method for examining and evaluating the current state of a process in order to identify opportunities for improvement in the future
Gauge chart: A data visualization that shows a single result within a progressive range of values
General Data Protection Regulation of the European Union (GDPR): Policy-making body in the European Union created to help protect people and their data
Geolocation: The geographical location of a person or device by means of digital information
Geom (R): The geometric object used to represent data
ggplot2 (R): An R package in Tidyverse that creates a variety of data visualizations by applying different visual properties to the data variables in R
Good data source: A data source that is reliable, original, comprehensive, current, and cited (ROCCC)
GROUP BY:
A SQL clause that groups rows that have the same values from a table into summary rows
HAVING: A SQL clause that adds a filter to a query instead of the underlying table that can only be used with aggregate functions
head() (R): An R function that returns a preview of the column names and the first few rows of a dataset
Header: The first row in a spreadsheet that labels the type of data in each column
Headline: Text at the top of a visualization that communicates the data being presented
Heat map: A data visualization that uses color contrast to compare categories in a dataset
Highlight table: A data visualization that uses conditional formatting and color on a table
Histogram: A data visualization that shows how often data values fall into certain ranges
HTML (Hypertext Markup Language): The set of markup symbols or codes used to create a webpage
HTML5: A programming language that provides structure for web pages and connects to hosting platforms
Hypothesis: A theory that one might try to prove or disprove with data
Hypothesis testing:
A process to determine if a survey or experiment has meaningful results
IDE (Integrated Development Environment): A software application that brings together all the tools a data analyst may want to use in a single place
Incomplete data: Data that is missing important fields
Inconsistent data: Data that uses different formats to represent the same thing
Incorrect/inaccurate data: Data that is complete but inaccurate
Inline code: Code that can be inserted directly into the text of an R Markdown file
INNER JOIN : A SQL function that returns records with matching values in both tables
Inner query: A SQL subquery that is inside of another SQL statement
Internal data: Data that lives within a company’s own systems
Interpretation bias: The tendency to interpret ambiguous situations in a positive or negative way
Java: A programming language widely used to create enterprise web applications that can run on multiple clients
JOIN: A SQL function that is used to combine rows from two or more tables based on a related column
Jupyter Notebook:
An open-source web application used to create and share documents that contain live code, equations, visualizations and narrative text
Label: Text in a visualization that identifies a value or describes a scale
Labels and annotations (R): A group of R functions used for customizing a plot
Leading question: A question that steers people toward a certain response
LEFT: A function that returns a set number of characters from the left side of a text string
LEFT JOIN: A SQL function that will return all the records from the left table and only the matching records from the right table
Legend: A tool that identifies the meaning of various elements in a data visualization
LEN: A function that returns the length of a text string by counting the number of characters it contains
Length: The number of characters in a text string
Library: A directory containing all of a data analyst’s installed packages
LIMIT: A SQL clause that specifies the maximum number of records returned in a query
Line graph: A data visualization that uses one or more lines to display shifts or changes in data over time
List: A vector whose elements can be of any type
Live data: Data that is automatically updated
Loess smoothing (R): A process used for smoothing plots with fewer than 1,000 points
Log file: A computer-generated file that records events from operating systems and other software programs
Logical operator: An operator that returns a logical data type
Long data: A dataset in which each row is one time point per subject, so each subject has data in multiple rows
Mandatory: A data value that cannot be left blank or empty
Map: A data visualization that organizes data geographically
Mapping (R): The process of matching up a specific variable in a dataset with a specific aesthetic
Margin of error: The maximum amount that sample results are expected to differ from those of the actual population
Markdown (R): A syntax for formatting plain text files
Mark: A visual object in a data visualization such as a point, line, or shape
MATCH: A spreadsheet function used to locate the position of a specific lookup value
Math expression: A calculation that involves addition, subtraction, multiplication, or division (also called an equation)
Math function: A function that is used as part of a mathematical formula
Matrix: A two-dimensional collection of data elements with rows and columns
MAX: A function that returns the largest numeric value from a range of cells
MAXIFS: A spreadsheet function that returns the maximum value from a given range that meets a specified condition
McCandless Method: A method for presenting data visualizations that moves from general to specific information
Measurable question: A question whose answers can be quantified and assessed
Mental model: A data analyst’s thought process and approach to a problem
Mentor: Someone who shares knowledge, skills, and experience to help another grow both professionally and personally
Merger: An agreement that unites two organizations into a single new one
Metadata: Data about data
Metadata repository: A database created to store metadata
Metric: A single, quantifiable type of data that is used for measurement
Metric goal: A measurable goal set by a company and evaluated using metrics
MID: A function that returns a segment from the middle of a text string
MIN: A spreadsheet function that returns the smallest numeric value from a range of cells
MINIFS: A spreadsheet function that returns the minimum value from a given range that meets a specified condition
Modulo: An operator (%) that returns the remainder when one number is divided by another
Movement: The design principle of arranging visual elements to guide the audience’s eyes from one part of a data visualization to another
mutate() (R): An R function that makes changes to a dataframe separating and merging columns or creating new variables
Naming conventions: Consistent guidelines that describe the content, creation date, and version of a file in its name
Narrative: (Refer to Story)
Nested: Code that performs a particular function and is contained within code that performs a broader function
Nested function: A function that is completely contained within another function
Networking: Building relationships by meeting people both in person and online
Nominal data: A type of qualitative data that is categorized without a set order
Normalized database: A database in which only related data is stored in each table
Notebook: An interactive, editable programming environment for creating data reports and showcasing data skills
Null: An indication that a value does not exist in a dataset
Observation: The attributes that describe a piece of data contained in a row of a table
Observer bias: The tendency for different people to observe things differently (also called experimenter bias)
Open data: Data that is available to the public
Open-source: Code that is freely available and may be modified and shared by the people who use it
Openness: The aspect of data ethics that promotes the free access, usage, and sharing of data
Operator: A symbol that names the operation or calculation to be performed
ORDER BY: A SQL clause that sorts results returned in a query
Order of operations: Using parentheses to group together spreadsheet values in order to clarify the order in which operations should be performed
Ordinal data: Qualitative data with a set order or scale
Outdated data: Any data that has been superseded by newer and more accurate information
OUTER JOIN: A SQL function that combines RIGHT and LEFT JOIN to return all matching records in both tables
Outer query: A SQL statement containing a subquery
Ownership: The aspect of data ethics that presumes individuals own the raw data they provide and have primary control over its usage, processing, and sharing
Package (R): A unit of reproducible R code
Packed bubble chart: A data visualization that displays data in clustered circles
Pattern: The design principle of using similar visual elements to demonstrate trends and relationships in a data visualization
PHP (Hypertext Preprocessor): A programming language for web application development
Pie chart: A data visualization that uses segments of a circle to represent the proportions of each data category compared to the whole
Pipe (R): A tool in R for expressing a sequence of multiple operations, represented with “%>%”
Pivot chart: A chart created from the fields in a pivot table
Pivot table: A data summarization tool used to sort, reorganize, group, count, total, or average data
Pixel: In digital imaging, a small area of illumination on a display screen that, when combined with other adjacent areas, forms a digital image
Population: In data analytics, all possible data values in a dataset
Portfolio: A collection of materials that can be shared with potential employers
Pre-attentive attributes: The elements of a data visualization that an audience recognizes automatically without conscious effort
Primary key: An identifier in a database that references a column in which each value is unique (Refer to foreign key)
Problem domain: The area of analysis that encompasses every activity affecting or affected by a problem
Problem types: The various problems that data analysts encounter, including categorizing things, discovering connections, finding patterns, identifying themes, making predictions, and spotting something unusual
Profit margin: A percentage that indicates how many cents of profit has been generated for each dollar of sale
Programming language: A system of words and symbols used to write instructions that computers follow
Proportion: The design principle of using the relative size and arrangement of visual elements to demonstrate information in a data visualization
Python: A general-purpose programming language
Qualitative data: A subjective and explanatory measure of a quality or characteristic
Quantitative data: A specific and objective measure, such as a number, quantity, or range
Query: A request for data or information from a database
Query language: A computer programming language used to communicate with a database
R: A programming language used for statistical analysis, visualization, and other data analysis~~~~
R Markdown: A file format for making dynamic documents with R
R Notebook: A document for running code and displaying the graphs and charts that visualize the code
Random sampling: A way of selecting a sample from a population so that every possible type of the sample has an equal chance of being chosen
Range: A collection of two or more cells in a spreadsheet
Ranking: A system to position values of a dataset within a scale of achievement or status
readr (R): An R package in Tidyverse used for importing data
Record: A collection of related data in a data table, usually synonymous with row
Redundancy: When the same piece of data is stored in two or more places
Reframing: The process of restating a problem or challenge, then redirecting it toward a potential resolution
Regular expression (RegEx): A rule that says the values in a table must match a prescribed pattern
Relational database: A database that contains a series of tables that can be connected to form relationships
Relational operator: An operator used to compare values, also known as a comparator
Relativity: The process of considering observations in relation or proportion to something else
Relevant question: A question that has significance to the problem to be solved
Remove duplicates: A spreadsheet tool that automatically searches for and eliminates duplicate entries from a spreadsheet
Repetition: The design principle of repeating visual elements to demonstrate meaning in a data visualization
Report: A static collection of data periodically given to stakeholders
Return on investment (ROI): A formula that uses the metrics of investment and profit to evaluate the success of an investment
Revenue: The total amount of income generated by the sale of goods or services
Rhythm: The design principle of creating movement and flow in a data visualization to engage an audience
RIGHT: A function that returns a set number of characters from the right side of a text string
RIGHT JOIN: A SQL function that will return all records from the right table and only the matching records from the left
Root cause: The reason why a problem occurs
ROUND: A SQL function that returns a number rounded to a certain number of decimal places.
Ruby: An object-oriented programming language for web application development
Sample: In data analytics, a segment of a population that is representative of the entire population
Sampling bias: Overrepresenting or underrepresenting certain members of a population as a result of working with a sample that is not representative of the population as a whole
Scatter plot: A data visualization that represents relationships between different variables with individual data points without a connecting line
Schema: A way of describing how something, such as data, is organized
Scope of work (SOW): An agreed-upon outline of the tasks to be performed during a project
Second-party data: Data collected by a group directly from its audience and then sold
SELECT: The section of a query that indicates from which column(s) to extract the data
SELECT INTO: A SQL clause that copies data from one table into a temporary table without adding the new table to the database
Shiny (R): An R package used to build interactive web apps with R code
Small data: Small, specific data points typically involving a short period of time, which are useful for making day-to-day decisions
SMART methodology: A tool for determining a question’s effectiveness based on whether it is specific, measurable, action-oriented, relevant, and time-bound
Smoothing (R): A process used to make data visualizations in R clearer and more readable
Smoothing line (R): A line on a data visualization that uses smoothing to represent a trend
Social media: Websites and applications through which users create and share content or participate in social networking
Soft skills: Nontechnical traits and behaviors that relate to how people work
Sort range: A spreadsheet menu function that sorts a specified range and preserves the cells outside the range
Sort sheet: A spreadsheet menu function that sorts all data by the ranking of a specific sorted column and keeps data together across rows
Sorting: The process of arranging data into a meaningful order to make it easier to understand, analyze, and visualize
Specific question: A question that is simple, significant, and focused on a single topic or a few closely related ideas
SPLIT: A spreadsheet function that divides text around a specified character and puts each fragment into a new, separate cell
Sponsor: A professional advocate who is committed to moving forward the career of another
Spotlightling: Scanning through data to quickly identify the most important insights
Spreadsheet: A digital worksheet
SQL: (Refer to Structured Query Language)
Stakeholders: People who invest time and resources into a project and are interested in its outcome
Static data: Data that doesn’t change once it has been recorded
Static visualization: A data visualization that does not change over time unless it is edited
Statistical power: The probability that a test of significance will recognize an effect that is present
Statistical significance: The probability that sample results are not due to random chance
Statistics: The study of how to collect, analyze, summarize, and present data
Story: The narrative of a data presentation that makes it meaningful and interesting
String data type: A sequence of characters and punctuation that contains textual information (also called text data type)
Structural metadata: Metadata that indicates how a piece of data is organized and whether it is part of one or more than one data collection
Structured data: Data organized in a certain format such as rows and columns
Structured Query Language: A computer programming language used to communicate with a database
Structured thinking: The process of recognizing the current problem or situation, organizing available information, revealing gaps and opportunities, and identifying options
Subquery: A SQL query that is nested inside a larger query
SUBSTR: A SQL function that extracts a substring from a string variable
Substring: A subset of a text string
Subtitle: Text that supports a headline by adding context and description
SUM: A spreadsheet function that adds the values of a selected range of cells
SUMIF: A spreadsheet function that adds numeric data based on one condition
Summary table: A table used to summarize statistical information about data
SUMPRODUCT: A function that multiplies arrays and returns the sum of those products
Swift: A programming language for macOS, iOS, watchOS, and tvOS
Symbol map: A data visualization that displays a mark over a given longitude and latitude
Syntax: The predetermined structure of a language that includes all required words, symbols, and punctuation, as well as their proper placement
Tableau: A business intelligence and analytics platform that helps people visualize, understand, and make decisions with data
Technical mindset: The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way
Temporary table: A database table that is created and exists temporarily on a database server
Text data type: A sequence of characters and punctuation that contains textual information (also called string data type)
Text string: A group of characters within a cell, most often composed of letters
Third-party data: Data provided from outside sources who didn’t collect it directly
Tibble (R): A streamlined variation of data frames
Tidy data (R): A way of standardizing the organization of data within R
tidyr (R): An R package in Tidyverse used for data cleaning to make tidy data
Tidyverse (R): A system of packages in R with a common design philosophy for data manipulation, exploration, and visualization
Time-bound question: A question that specifies a timeframe to be studied
Transaction transparency: The aspect of data ethics that presumes all data-processing activities and algorithms should be explainable and understood by the individual who provides the data
Transferable skills: Skills and qualities that can transfer from one job or industry to another
TRIM: A function that removes leading, trailing, and repeated spaces in data
TSV (Tab-separated values file): A text file that stores a data table by separating columns of data with tabs
Turnover rate: The rate at which employees voluntarily leave a company
Typecasting: Converting data from one type to another
Unbiased sampling: When the sample of the population being measured is representative of the population as a whole
Underscores: Lines used to underline words and connect text characters
Unfair question: A question that makes assumptions or is difficult to answer honestly
Unique: A value that can’t have a duplicate
United States Census Bureau: An agency in the U.S. Department of Commerce that serves as the nation’s leading provider of quality data about its people and economy
Unity: The design principle of using visual elements that complement each other to create aesthetic appeal and clarity in a data visualization
Unstructured data: Data that is not organized in any easily identifiable manner
Validity: The degree to which data conforms to constraints when it is input, collected, or created
VALUE: A spreadsheet function that converts a text string that represents a number to a numeric value
Variable (R): A representation of a value in R that can be stored for later use
Variety: The design principle of using different kinds of visual elements in a data visualization to engage an audience
Vector (R): A group of data elements of the same type stored in a one-dimensional sequence in R
Verification: A process to confirm that a data-cleaning effort was well executed and the resulting data is accurate and reliable
Video file: A collection of images, audio files, and other data usually encoded in a compressed format such as MP4, MV4, MOV, AVI, or FLV
Vignette (R): Documentation for an R package that describes the problem the package is designed to solve, explains how its functions can be used, and lists any dependencies on other packages
Visual form: The appearance of a data visualization that gives it structure and aesthetic appeal
Visualization: (Refer to Data visualization)
VLOOKUP: A spreadsheet function that vertically searches for a certain value in a column to return a corresponding piece of information
WHERE: The section of a query ****that specifies criteria that the requested data must meet
Wide data: A dataset in which every data subject has a single row with multiple columns to hold the values of various attributes of the subject
WITH: A SQL clause that creates a temporary table that can be queried multiple times
World Health Organization: An organization whose primary role is to direct and coordinate international health within the United Nations system
X-axis: The horizontal line of a graph usually placed at the bottom, which is often used to represent time scales and discrete categories
Y-axis: The vertical line of a graph usually placed to the left, which is often used to represent frequencies and other numerical variables
YAML: A language that translates data to improve readability
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