ACCT 3025 Exam 1
what does volume refer to?
size
what are the 8 different approaches to the data to answer the question?
-classification -regression -similarity matching -clustering -co-occurrence grouping -profiling -link prediction -data reduction
what are diagnostic analytics?
procedures that explore the current data to determine why something has happened the way it has, typically comparing the data to a benchmark
what are prescriptive analytics?
procedures that model data to enable recommendations for what should be done in the future
what are descriptive analytics?
procedures that summarize existing data to determine what has happened in the past
what are predictive analytics?
procedures used to generate a model that can be used to determine what is likely to happen in the future
what is step 6 in the IMPACT model?
track outcomes
what does step 1 mean?
understand the business problems that need to be addressed
what might clustering be used for?
used to segment loyalty card customers into groups based on buying behavior related to shopping frequency or purchasing volume for additional analysis and marketing activities
what does velocity refer to?
frequency
what are composite keys?
combination of 2 foreign keys used for line items
what is a class?
a manually assigned category applied to a record based on an event
what is step 3 in requesting data?
validate the data for completeness and integrity
how would an analysts help summarize what has happened in the past?
would count the number of records in a data extract to ensure the data are complete before running a more complex analysis
how would an auditor help summarize what has happened in the past?
would filter data to limit the scope to transactions that represent the highest risk
how would a financial accountant help summarize what has happened in the past?
would sum all the sales transactions within a period to calculate the value for sales revenue that appears on the income statement
what does load the data for data analysis (step 5) mean?
you can now import your data into the tool of your choice and expect the functions to work properly
What is a data dictionary?
-A centralized repository of information about data that includes such as elements as meaning, relationships to other data, usage and format. -define what data are acceptable
what are the questions in obtain the data (step 2)?
-How will data be requested and/or obtained? -Do you have access to the data yourself, or do you need to request a database administrator or the information systems department to provide the data for you? -if you need to request the data, is there a standard data request form that you should use? -From whom do you request the data? -Where are the data located in the financial or other related systems? -What specific data are needed (tables and fields)? -What tools will be used to perform data analytic tests or procedures and why?
what is structured query language (SQL)?
-a computer language to interact with data in a database by creating, updating, deleting, and extracting -can combine data from one or more tables and organize the data in a way that is more intuitive and useful for data analysis than the way the data are stored in the relational database
How does data analytics affect financial reporting?
-accountants make better estimated of collectability, write-downs etc. -managers better understand the business environment through social media -analysts identify risks and opportunities through analysis of internet searches
what do internal data sources include?
-accounting information system -supply chain management system -customer relationship management system -human resource management system
What is classification?
-an attempt to assign each unit (or individual) in a population into a few categories -examples: of all the loans this bank has offered, which are most likely default? which loan applications are expected to be approved? which transactions would a credit card company flag as potentially being fraudulent and deny payment? which companies are most likely to go bankrupt in the next 2 years?
what is profiling?
-an attempt to characterize the "typical" behavior of an individual, group, or population by generating summary statistics about the data (including mean, median, minimum, maximum, and standard deviation) -done primarily using structured data -generally performed on data that are readily available -used to discover patterns of behavior
what is clustering?
-an attempt to divide individuals (like customers) into groups (or clusters) in a useful or meaningful way -identifying groups of similar data elements and the underlying drivers of those groups -clustering algorithms calculate the minimum distance of all observations and groups those elements
what is a customer relationship management system?
-an information system for overseeing all interactions with current and potential customers with the goal of improving relationships -contains every detail about the customer
what do accountants need to be able to do?
-articulate business problems -communicate with data scientists -draw appropriate conclusions -present results in an accessible manner -develop an analytics mindset
what are foreign keys?
-attributes that point to a primary key in another table -attribute that exists in relational databases in order to carry out the relationship between 2 tables -does not serve as the "unique identifier" -must be identified when mastering the data from a relational database in order to extract the data correctly from more than one table
what does validate the data for completeness and integrity (step 3) mean?
-chances are the data you request is not complete -before you begin, do a little work to make sure your data are valid: compare the number of records, compare descriptive statistics for numeric fields, validate date/time fields, compare string limits for text fields
what is power automate good for?
-collect data from multiple sources -robotics process automation
how does data analytics affect tax?
-companies develop sophisticated tax planning strategies -managers understand tax consequences of international transactions, investment, mergers, and acquisitions -the organization understands tax tables and other tax data to aid compliance
what do relational databases ensure?
-data are complete or include all data -data are no redundant, so they don't take up too much space -data follow business rules and internal controls -data aid communication and integration of business processes
what should accountants also be comfortable with?
-data scrubbing and data preparation -data quality -descriptive data analysis -data analysis through data manipulation -define and address problems through statistical analysis -data visualization and data reporting
what is structured data?
-data that are organized and reside in a fixed field with a record or a file -generally contained in a relational database or spreadsheet -readily searchable by search algorithms
what are prescriptive analytics examples?
-decision support systems -machine learning and artificial intelligence
what are the 4 categories of data analytics?
-descriptive analytics -diagnostic analytics -predictive analytics -prescriptive analytics
what are some examples of regression?
-employee turnover -allowance for loan losses amount
How does data analytics affect auditing?
-enhances audit quality -enables enhanced audits, expanded services, and added value to clients -external auditors will stay engaged beyond the audit
How does data analytics affect management accounting?
-enhances cost analysis -enables better decision-making -enables better forecasting, budgeting, production, and sales
what does the Microsoft track include?
-excel -power query -power BI -power automate
what does step 6 mean?
-follow up on the results of the analysis -how frequently should the analysis be preformed? -have the analytics changed? -what are the trends?
what does step 4 mean?
-identify issues with the analyses, possible issues, and refine the model -ask further questions -test hypotheses -explore the data -rerun analyses -slice, dice, and manipulate the data -find correlations
what steps does data reduction involve?
-identify the attribute you would like to reduce or focus on -filter the results -interpret the results -follow up on the results
what are the general steps of classification?
-identify the classes you wish to predict -manually classify an existing set of records -select a set of classification models -divide your data into training and testing sets -generate your model -interpret the results and select the "best" model
what are the general steps of profiling?
-identify the objects or activity you want to profile -determine the types of profiling you want to preform -set boundaries or thresholds for the activity -interpret the results and monitor the activity and/or generate a list of exceptions -follow up in exceptions
what are the general steps in regression?
-identify the variables that might predict an outcome -determine the functional form of the relationship -identify the parameters of the model -dependent variable = f(independent variable)
what are descriptive attributes?
-include everything else -attributes that exist in relational databases that are neither primary or foreign keys -provide business information, but are not required to build a database -examples: "company name", "employee address"
what are some data available in step 2?
-internal ERP systems -external networks and data warehouses -data dictionaries (provide details about the data) -extraction, transformation, and loading -data validation and completeness (provide a sense of reliability of the data) -data normalization (to reduce data redundancy and improve data integrity) -data preparation and scrubbing
what is power BI good for?
-large datasets -advanced visualization -dashboards -presentation
what is tableau desktop good for?
-large datasets -advanced visualization -dashboards -presentation
what is power query good for?
-large datasets -data joining -data cleaning -data transformation
what is tableau prep builder good for?
-large datasets -data summarization -data joining -data cleaning -data transformation
what are the methods in obtain the data (step 2)?
-obtain the data through a data request to the IT department -obtain data yourself: If you have direct access to a data warehouse, you can use SQL and other tools to pull the data yourself, Identify the tables that contain the information you need. You can do this by looking through the data dictionary or the relationship model, Identify which attributes, specifically, hold the information you need in each table, Identify how those tables are related to each other.
what does clean the data (step 4) mean?
-once you have valid data, there is some work that needs to be done to make sure it is consistent and ready for analysis: remove headings or subtotals, clean leading zeros and nonprintable characters, format negative numbers, correct inconsistencies across data in general
what are the 4 types of attributes of a table?
-primary keys -foreign keys -composite keys -descriptive attributes
what are diagnostic analytics examples?
-profiling -clustering -similarity matching -co-occurrence grouping
what are predictive analytics examples?
-regression -classification -link prediction
what is excel good for?
-small datasets -data tables -pivot tables -basic visualization
what are descriptive analytics examples?
-summary statistics -data reduction or filtering
what does the tableau track include?
-tableau prep builder -tableau desktop -tableau public
what are primary keys?
-unique to identifiers -required to exist in each table of a relational database -typically made up of one column -rarely truly descriptive; a collection of letters or simply sequential numbers are often used -examples: student ID number, amazon order numbers, invoice numbers, account numbers, social security, driver license number
what is data reduction or filtering?
-used to reduce the amount of observations to focus on relevant items -does this by taking a large set of data and reducing it to a smaller set that has the vast majority of the critical information of the larger set
what is an example of profiling?
-variance analysis -managers use profiling to compare variances from target ranges
what are the for 4V's?
-volume -velocity -variety -veracity
for data dictionaries, what do we learn for each attribute?
-what type of key it is -what data are required -what data can be stored in -how much data is stored
what is a flat file?
a means of storing data in one place, as opposed to storing the data in multiple tables
what is enterprise resource planning (ERP)?
a category of business management software that integrates applications from through out the business
what is data reduction?
a data approach that attempts to reduce the amount of information that needs to be considered to focus on the most critical items
What is regression?
a data approach used to predict a specific dependent variable value based on independent variable inputs using a statistical model
what is an accounting information system?
a system that records, processes, reports, and communicates the results of business transactions to provide financial and nonfinancial information for decision-making purposes
what does effective data analytics provide?
a way to search through large structured and unstructured data to identify unknown patterns or relationships
what is similarity matching?
an attempt to identify similar individuals based on data known about them
what is step 4 in the IMPACT model?
address and refine results
what is co-occurrence grouping?
an attempt to discover associations between individuals based on transactions involving them
what is link prediction?
an attempt to predict connections between 2 data items
what is a target?
an expected attribute that we want to evaluate
what do potential ethical issues include?
an individual's right to privacy and whether assurance is offered that certain date are not misused
what is a human resource management system?
an information system for managing all interactions with current and potential employees
what is tableau public good for?
analyze and share public datasets
what does determine the purpose and scope of the data request (step 1) mean?
ask a few questions before beginning the process: -what is the purpose of the data request? -what do you need the data to solve? -what business problem will it address? -what risk exists in data integrity? -what is the mitigation plan? -what other information will impact the nature, timing, and extent of the data analysis?
what does step 5 mean?
communicate effectively using clear language and visualizations: dashboards, static reports, and summaries
what is step 5 in the IMPACT model?
communicate insights
what is step 4 in requesting data?
clean the data
What is unstructured data?
data that do not adhere to a predefined data model in a tabular format
What is big data?
datasets that are too large and complex to be analyzed traditionally
what is summary statistics?
describe a set of data in terms of their location (mean, median), range (standard deviation, minimum, maximum), shape (quartile), and size (count)
what is step 1 in requesting data?
determine the purpose an scope of the data request
what does variety refer to?
different types
What is step 1 in the IMPACT model?
identify the questions
what is a supply chain management system?
includes information on active vendors, the orders made to date, or demand schedules for what component of the final product is needed when
what does step 2 mean?
know what data are available and how they relate to the problem
what are machine learning and artificial intelligence?
learning models or intelligent agents that adapt to new external data to recommend a course of action
what is step 5 in requesting data?
load the data for data analysis
what is step 2 in the IMPACT model?
master the data
what is step 2 in requesting data?
obtain the data
what is step 3 in the IMPACT model?
perform the test plan
what is a decision support system?
rule-based systems that gather data and recommend actions based on the input
what does step 3 mean?
select an appropriate model to find a target variable
what does veracity refer to?
the data quality
what is data analytics?
the process of evaluating data with the purpose of drawing conclusions to address business questions
when might a company use similarity matching?
to find new customers that may closely resemble their best customers (in hopes they find additional profitable customers)
