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Acct 4701 Exam 1 Voc
| Question | Answer |
|---|---|
| Volume | Amount of data generated and stored |
| Variety | Types of data |
| Velocity | How fast is the data generated and processed |
| Veracity | Refers to data quality and reliability |
| Structured data | stored in fixed rows and columns |
| Semi Structured Data | with no predefined structure, but not fixed rows or columns |
| Unstructured Data | data with no predefined structure, cannot be easily stored in tables with out significant processing |
| Financial Statements | Aren't always truthful, and often contain estimates |
| Budget Data | Predictions on how much things will cost |
| Standard Cost data | Allows variance analysis comparing to budget to actual |
| Point of Sale Transaction Data | All info from sale |
| Potential Cost Drivers | Allows evaluation of best way to allocate overhead |
| Supply Chain Data | System which tracks products from vendor to final customer |
| Customer Relationship Management System Data | Tracks everything about customer |
| HR Management System Data | System which tracks all info regarding employees |
| Categorical | Represented by words |
| Example of Categorical | Gender or transaction |
| Numerical | Numbers |
| Example of Numerical | Exam Scores |
| Nominal Data | Categorical data, can not be ranked |
| Ordinal Data | Categorical data that allows/implies ranking and sorting |
| Interval Data | An equal interval between each observation so that not only does summing the data makes sense so does multiplication and other complex numerical calculations |
| Ratio Data | Numerical data with an equal and definitive ratio between each data point and absolute 0 in ration data is the point of origin |
| Data Dictionary | a centralized repository of info about data containing a separate record for each field/variable in the table/database |
| Excel | Best at data analysis and exploring data |
| Tableau Desktop | Best for data visualization, does not allow original data entry |
| Databases | Must secure method of string data |
| Relational Databases | Instead of storing all data required for analysis in massive table, break the data into separate tables |
| Entity Relationship | Graphical representation of an information system, illustrating relationships among people, objects, places and events within that system |
| Descriptive analysis answers | What happened? |
| Diagnostic analysis answers | Why did it happen? |
| Predictive analysis answers | Will it happen in the future? |
| Prescriptive analysis answers | What should we do based on? What we expect will happen? |
| Descriptive Analysis | the foundational process of summarizing and interpreting historical financial data to explain past performance |
| Diagnostic Analysis | the process of examining financial data to determine the root causes of trends, anomalies, or performance outcomes |
| Predictive Analysis | uses historical financial data, statistical modeling, and machine learning to forecast future financial outcomes, risks, and trends |
| Prescriptive Analysis | the most advanced form of data analytics that uses historical data, machine learning, and algorithms to recommend specific, optimal actions to achieve desired future financial results |
| Null Hypothesis | No difference |
| Alternate hypothesis | Opposite of null |
| P-value | Probability of observing data, compared to threshold value called significant level (or alpha) |
| Common Alpha Value | 5% |
| Confidence Interval | Range of values likely to contain the true population value |
| If p-value < 5% | Can reject null hypothesis |
| If p-value > 5% | Failed to reject hypothesis |
| Mean, Median, Mode | Central tendency |
| Minimums, Maximums | Extreme Values |
| Standard Deviation | Data variability |
| Quartiles/Deciles | Divide data obs into intervals |
| Percent Change | (New - Old)/Old |
| Tables | Exact values and detailed information |
| Charts | Patterns, Trends, or comparisons |
| Horizontal Analysis | Provides comparative increases about various |
| Vertical Analysis | Expresses financial info in relation to some figures or a base |
| Return on Equity (ROE) | =Net income/Equity =Profit Margin*Asset Turnover*Equity Multiplier =(Net Income/Sales)*(Sales/Total Assets)*(Total Assets/Equity) |
| Outlier | Statistical term - refers to data point that lies far outside the expected distribution |
| Anomaly | Broader concept - refers to something unusual or unexpected |
Created by:
c22shaferv