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Glossary
Data Analytics
Terms and Definitions
Terms and definitions from all courses
A
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 B 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
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 that 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 D 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 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 E 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
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 G 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 H 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 I 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 J 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
M 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 spreadsheet 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 N 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 O 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
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 Q 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 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
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 T 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 that did not 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
