Accounting Analytics Test 1 - Chapter 1

The process of data analytics aims to? (What is Data Analytics?)

transform raw data into knowledge to create value

What does perform the test plan mean? (3rd step - IMPACT cycle) How do we usually do this?

1. Being able to determine the right approach to the data 2. Generally we make a model

What does communicate insights mean? (5th step - IMPACT cycle) What are some examples of this? (3)

1. Communicate effectively using clear language and visualizations 2. Static reports, digital dashboards, and data visualizations

What are the first 4 data analytic skills needed by accountants?

1. Develop an analytics mindset - recognize when and how data analytics can address business questions 2. Data scrubbing and data preparation - comprehend the process needed to clean and prepare the data before analysis 3. Data quality - Recognize what is meant by data quality, be it completeness, reliability, or validity 4. Descriptive data analysis - Perform basic analysis to understand the quality of the underlying data and its ability to address the business question

(2nd step - Master the data) We need to know everything about the data, including? (4)

1. How to access it 2. Availability 3. reliability 4. What time periods are covered

What does address and refine results mean? (4th step - IMPACT cycle) What ways do we do this? (3)

1. Identify issues with the analyses, possible issues, and refine the model 2. Ask further questions, explore the data, re-run analyses

What are the steps in the Impact Cycle? (6)

1. Identify the questions 2. Master the data 3. Perform test plan 4. Address and refine results 5. Communicate insights 6. Track outcomes

What are 4 V's used to describe Big Data? (What is Big Data?)

1. Volume - Sheer size of the database 2. Velocity - the speed of the data processing (frequency) 3. Variety - The number of types of data 4. Veracity - the quality of the data being analyzed

(1st-step Identify the questions) Questions can? Having a?

1. arise from many sources 2. concrete, specific question that is potentially answerable by data analytics is an important first step

What does the identify the question mean? (1st step of IMPACT Cycle)

Being able to understand the business problem that needs addressing

What are the last 3 data analytic skills needed by accountants?

5. Data analysis through data manipulation - demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis 6. Define and address problems through statistical data analysis - identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis 7. Data visualization and data reporting - report results of analysis in an accessible way to each varied decision maker and his or her specific needs

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is Co-occurrence Grouping? (3rd step - IMPACT Cycle)

A data approach that attempts to discover associations between individuals based on transactions involving them (Amazon might use this to sell another item to you by knowing what items are "frequently bought together" or "Customers who bought this item also bought...")

What is Big Data?

Datasets that are too large and complex for business existing systems to handle utilizing their traditional capabilities to capture, store, manage, and analyze these datasets

What crucial Data analytics process is apart of the Master the Data step in the IMPACT cycle?

ETL process (Extract, transform, load)

What does track outcomes mean? (6th step - IMPACT cycle)

Follow up on the results from your analysis (What are the trends?)

(3rd step - IMPACT Cycle) Using all available data, we see if we can identify a?

Relationship between the response or dependent variables and those items that affect the response (predictors, explanatory, or independent variables)

What does master the data mean? (2nd step - IMPACT cycle)

Requires one to know what data are available and whether those data might be able to help address the business problem

What is Data Analytics?

The process of evaluating data with the purpose of drawing conclusions to address business questions

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is classification analysis? (3rd step - IMPACT Cycle)

a data approach that attempts to assign each unit in a population into a few categories potentially to help with predictions (Ex: Of all the loans this bank has approved, which are most likely to default? Or which loan applications are expected to be approved? Or which transactions would a credit card company potentially flag as fraud?)

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is Profiling analysis? (3rd step - IMPACT Cycle)

a data approach that attempts to characterize the "typical" behavior of an individual, group, or population by generating summary statistics about the data (including mean, standard deviation, etc.).

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is clustering analysis? (3rd step - IMPACT Cycle)

a data approach that attempts to divide individuals (like customers) into groups (or clusters) in a useful or meaningful way.

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is similarity matching? (3rd step - IMPACT Cycle)

a data approach that attempts to identify similar individuals based on data known about them. (Ex: Identifying seller and customer fraud based on various characteristics known about them to see if they were similar to the fraud cases. Reference the Alibaba example at the very beginning of the chapter, for more info.)

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is Regression analysis? (3rd step - IMPACT Cycle)

a data approach used to predict a specific dependent variable value based on independent variable inputs using a statistical model. (Ex:Given a balance of total accounts receivable held by a firm, what is the appropriate level of allowance for doubtful accounts for bad debts?)

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is Link Prediction analysis? (3rd step - IMPACT Cycle)

an attempt to predict a relationship between two data items. This might be used in social media. (Ex: An individual may have 22 mutual Facebook friends with me and we both attended BYU, is there a chance we would like to be Facebook friends as well? In an accounting setting, link prediction may be used to look for relationships between related parties that are not otherwise disclosed.)

The research question, the model, the data availability, and the expected statistical inference may all suggest the use of different data approaches: What is Data Reduction? (3rd step - IMPACT Cycle)

attempts to reduce the amount of info that needs to be considered to focus on the most critical items (i.e., highest cost, highest risk, largest impact). It does this by taking a large data set and reducing it with a smaller set that has the vast majority of the critical info of the larger set. (Ex: While auditing has employed various random and stratified sampling over the years, Data Analytics suggests new ways to highlight which transactions do not need the same level of vetting as the other transactions.)

Data analytics is especially interested in reporting results to help? (5th step - Communicate insights)

decision makers see the data in an all-new way

Effective data analytics provides a way to search through? (What is Data Analytics?)

large structured and unstructured data to discover unknown patterns or relationships