Accounting Data Analytics, Chapter 1: "Data and Analytics in the Accounting Profession" flashcards

Data

(1.1) Raw figures and facts.

Information

(1.1) A form of data that has been transformed into knowledge through technology.

Data Analytics

(1.1) The process of analyzing raw data to answer questions or provide insights.

Self-Service Business Intelligence (SSBI) software

(1.1) Easy-to-use, accessible software that can prepare data, analyze data, and report results.

Dashboard

(1.1) A graphical user interface that shows key performance indicators for an organization.

Plan

(1.2) A stage of the DA process which involves identifying the motivation for the analysis, determining the objective and questions to answer, and devising a strategy to perform the analysis.

Motivation

(1.2) The reason a data analysis is being performed.

Internal Motivation

(1.2) The self-driven desire to uncover insights, solve problems, and create value from data without relying on external rewards.

External Motivation

(1.2) The drive to analyze and interpret data in response to outside rewards, recognition, or requirements such as career advancement, grades, or organizational goals.

Objective

(1.2) The goal of a data analysis project.

Strategy

(1.2) The intentional plan for collecting, processing, and interpreting data to guide decisions and achieve specific goals.

Internal Data

(1.2) Information generated within an organization.

External Data

(1.2) Information collected from outside an organization.

Analyze

(1.2) A step in the DA process involving applying analytical methods and tools to financial data to identify patterns, relationships, and insights that support decision-making.

Descriptive Method

(1.2) A DA method that investigates what is happening currently, or has occurred in the past.

Diagnostic Method

(1.2) A DA method that helps understand why something has happened.

Predictive Method

(1.2) A DA method that forecasts what might happen in the future.

Prescriptive Method

(1.2) A DA method that helps understand what should happen to meet goals and objectives.

Data Preparation

(1.2) The process of collecting, cleaning, and organizing financial data to ensure accuracy and consistency before analysis.

Extract

(1.2) A step of data preparation that involves retrieving the data from a source.

Transform

(1.2) A step of data preparation that involves cleaning, restructuring, and/or integrating data prior to using it for analysis.

Load

(1.2) A process within data preparation when transformed data are imported into the SSBI to perform analyses.

Information Modeling

(1.2) A step in the DA “analyze” stage that involves creating necessary information for analysis purposes, starting from the data collected.

Explore the Data

(1.2) A step in the DA “analyze” stage, that allows accountants to discover, question, and investigate data relationships to successfully execute data analysis objectives.

Report

(1.2) A stage of the DA process that determines if the analyses meet the project’s objectives, then shares results.

Interpret the Analysis

(1.2) A step in the “report” DA stage where analyses are reviewed to ensure they make sense based on the project’s objective, and that the results are valid and reliable.

Communicate Effectively

(1.2) A step in the “report” DA stage that involves communicating results orally, with visuals, or in writing.

Data Analytics Mindset

(1.3) The professional habit of critically thinking throughout the data analysis process before making and communicating a professional choice or decision.

Critical Thinking

(1.3) The skill of using disciplined reasoning to investigate, understand, and evaluate an event, opportunity, or issue.

Data Literacy

(1.3) The skill of understanding and communicating data.

Technological Agility

(1.3) The skill of being aware of technological developments, and being willing to try new things.

Communication Skills

(1.3) The skill of communicating DA results effectively.

Reasoning

(1.3) The human process of logically forming conclusions, judgments, or inferences from facts.

Analysis Risk

(1.4) A DA risk that involves choosing an inappropriate method, or applying an analysis method incorrectly.

Assumptions

(1.4) A DA risk that involves not understanding or evaluating the assumptions about the data or results.

Biases

(1.4) A DA risk that involves inappropriately using mental shortcuts that affect decisions.

Data Risk

(1.4) A DA risk that involves choosing inappropriate, incomplete, or incorrect data.

Understand the Stakeholders

(1.4) The process of using a DA mindset to identify who will use the analysis to tailor insights to their needs and objectives.

Identify the Purpose

(1.4) The process of using a DA mindset to define the specific goal or question the analysis aims to answer. This helps guide accurate and relevant insights.

Consider Alternatives

(1.4) The process of using a DA mindset to evaluate different sources, methods, assumptions, and scenarios to validate results and choose the most decision-useful approach.

Assess Risks

(1.4) The process of using a DA mindset to identify potential errors, biases, or limitations in the data and analysis that could impact the reliability of insights.

Identify Knowledge

(1.4) The process of using a DA mindset to determine key insights, patterns, or information gained from the data that supports information decision-making.

Perform Self-Reflection

(1.4) The process of using a DA mindset to evaluate the effectiveness of the analysis process and results to identify improvements for future decision-making.