CH 4-6 :((

data warehouse

a repository of data accumulated from internal and external data sources, including financial data, to help management decision making.

flat file

a single table of data with user- defined attributes that is stored separately from any application.

standard normal distribution

a special case of the normal distribution used for standardizing data. the standard normal distribution has 0 for its mean ( and thus for its mode and median too) and 1 for its standard deviation

normal distribution

a type of distribution in which the median, mean and mode are all equal, so half of all the observations fall below the mean and the other half above the mean. this phenomenon is naturally occurring in many datasets in our world, suck SAT scores and heights and weights of newborns. when datasets follow a normal distribution, they can be standardized and compared for easier analysis

monetary unit sampling (MUS)

allows auditors to evaluate account balances. MUS is more likely to pull accounts with large balances (higher risk and exposure) because it focuses on dollars, not account numbers.

predictive analytics

attempt to find hidden patterns or variables that are linked to abnormal behavior.

computer-assisted audit techniques (CAATs)

automated scripts that can be used to validate data, test controls, and enable substantive testing of transaction details or account balances and generate supporting evidence for the audit.

qualitative data

categorical data. all you can do with these data are count and group, and in some cases, you can rank the data. Qualitative data an be further dined in two ways; nominal data and ordinal data. there are not as many options for charting qualitative data because they are not as sophisticated as quantitative data.

audit data standards (ADSs)

define common tables and fields that are needed by auditors to perform common audit tasks. the AICPA developed these standards.

fuzzy matching

finds matches that may be less than 100% matching by finding correspondences between portions of the text or other entries

diagnostic analytics

looks for correlations or patterns of interest in the data

declarative visualizations

made when the aim of your project is to "declare" or present your findings to an audience. charts that are declarative are typically made after the data analysis has been completed and are meant to exhibit what was found in the analysis steps.

exploratory visualizations

made when the lines between steps P (perform test plan), A (address and refine results), and C (communicate results) are not as clearly divided as they are in a declaratize visialtuob project. often when you are exploring the data with visualizations, you are performing the test plan directly in visualization software like Tableau instead of creating the chart after the analysis has been done.

systems translator software

maps the various tables and fields from varied ERP systems into a consistent format.

quantitative data

more complex than qualitative data. quantitative data can be further defined in two ways; interval and ration. in all quantitative data, the intervals between data points are meaningful, allowing data to be not just counted, grouped, and ranked, but also to have more complex operations performed in them such as mean, median, and standard deviation

discrete data

one way to categorize quantitative data, as opposed to continuous data. discrete data are represented by whole numbers. ex- point in a basketball game

continuous data

one way to categorize quantitative data, as opposed to discrete data. continuous data can take on any value within a range. ex- height

heterogeneous systems approach

represent multiple installations or instances of a system. it would be considered the opposite of a homo system

homogeneous systems approach

represent one single installation or instance of a system. it would be considered the opposite of a heterogeneous system.

descriptive analytics

summarize activity or master data elements based on certain attributes.

Nominal Data

the least sophisticated type of data on the scale of nominal, ordinal, interval and ratio; a type of qualitative data. the only thing you can do with nominal data is count, group and take a proportion. ex- hair color, gender, and ethnic groups

standardization

the method used for comparing two datasets that follow the normal distribution. by using a formula, every normal distribution can be transformed into the standard normal distribution. if you standardize both datasets, you can place both distributions on the same chart and more swiftly come to your insights.

ratio data

the most sophisticated type of data on the scale of nominal, ordinal, interval, and ration; a type of quantitative data. they can be counted and grouped just like qualitative data, and the differences between each data point are meaningful like with interval data. additionally, ratio data have a meaningful0. in other words, once a dataset approached 0, 0 means the absence of. ex-currency

proportion

the primary statistic used with quantitative data. proportion is calculated by counting the number of items in a particular category, then dividing the number by the total number of observations.

ordinal data

the second most sophisticated type of data on the scale of nominal, ordinal, interval, and ratio; a type of qualitative data. ordinal can be counted and categorized like nominal data and the categories can also be ranked. ex- gold, silver, and bronze medals.

Interval Data

the third most sofhistocated type of data on the scale of nominal, ordinal, interval, and ration; a type of quantitative data. interval data can be counted and grouped like qualitative data, 0 does not mean "the absence of" but is simply another number. ex- fahrenheit scale of temperate measurement

production/live systems

those active systems that collect and report and are directly affected by current transactions

prescriptive analytics

use machine learning and artificial intelligence for auditors as decision support to assist future auditors in finding potential issues in the audit