CMA Part 1 - Section F
🇬🇧
In English
In English
Practice Known Questions
Stay up to date with your due questions
Complete 5 questions to enable practice
Exams
Exam: Test your skills
Test your skills in exam mode
Learn New Questions
Manual Mode [BETA]
The course owner has not enabled manual mode
Specific modes
Learn with flashcards
Complete the sentence
multiple choiceMultiple choice mode
SpeakingAnswer with voice
TypingTyping only mode
CMA Part 1 - Section F - Leaderboard
CMA Part 1 - Section F - Details
Levels:
Questions:
83 questions
| 🇬🇧 | 🇬🇧 |
| Database mapping facility | Software that is used to evaluate and document the structure of the database |
| A single-function systems (opposite of ERP) | Stovepipe systems |
| Object-oriented database | Response to the need to store not only numbers and characters but also graphics and multimedia applications |
| Online analytical processing (OLAP) | Also called multidimensional data analysis, which is the ability to analyze large amounts of data from numerous perspectives |
| Data warehouse | Contains historical as well as current operating data. READ-ONLY function |
| Data Mart | Subset of data warehouse, created for individual busines lines or department |
| Data cleansing | Cleans up data in a database that is incorrect, incomplete or duplicated |
| Data mining | The process of analyzing data from different perspective and summarizing it into useful information |
| Organize data in a conceptual arrangement | Relational Database Structure |
| Describes one attribute of an item or entity | Field / Column |
| Set of common records | File (table) |
| Makes up several related files/tables | Complete database |
| For a record to be entered in a given table, there must already be a record in some other table(s) | Referential integrity |
| Duplicates data to be stored at multiple locations | Replication / snapshot |
| Stores specific records where they are most needed | Fragmentation / partitioning |
| Describes both the physical and logical characteristics of every data element in a database | Data dictionary |
| A program used to display graphs and reports, changed, and otherwise controlled data from a relational database | Query Management Facility (QMF) |
| Software that is used to evaluate and document the structure of the database | Database mapping facility |
| Response to the need to store not only numbers and characters but also graphics and multimedia applications | Object-oriented database |
| The ability to analyze large amounts of data from numerous perspectives | Online analytical processing (OLAP) / multidimensional data analysis |
| The process of analyzing data from different perspective and summarizing it into useful information | Data mining |
| Corporate/business performance management | Enterprise Performance Management (EPM |
| Measures performance using capability and maturity levels | COBIT performance Management (CPM) model |
| Methodology applied to the development of large, highly structured application systems. | System Development Life Cycle (SDLC) |
| Quality control method which executes programmed code | Dynamic Testing |
| Tests the internal structures or workings of a program | White-box testing |
| Focuses on how well the software works. Examines functionality without any knowledge of the source code supporting the program | Black-box testing |
| Focuses on how well the software works. Evaluation involves having knowledge of the program’s internal data structures and algorithm | Gray-box testing |
| The relevant control in the process of managing changes in applications/system | Program Change Control |
| Rethinking of how business functions are performed to provide value to customer | Business Process Reengineering |
| A form of machine learning technology that enables a computer to acquire knowledge and mimic the actions of the person(s) using it to perform tasks | Robotic Process Automation (RPA) |
| Computer software designed to perceive, reason, and understand | Artificial Intelligence (AI) |
| Process information much like the human brain | Neural networks AI |
| Type of AI which learn from previous, similar experiences | Case-based reasoning systems |
| Type of AI which function on the basis of set rules | Rule-based expert systems |
| Built-in or learned knowledge base to execute a specific, repetitive, and predictable tasks | Intelligent agents |
| Is a measure of the FIT between the independent and dependent variables | Coefficient of determination (r2) |
| Assist with determining whether the sample is representative of the population | Goodness-of-fit test |
| Is the percentage of times that a sample is expected to be representative of the population | Confidence level |
| The range around a sample value that is expected to contain the true population value. | Confidence interval |
| Uses trial and error to determine the effects of changes in variable | Sensitivity Analysis |
| Generate the individual values for a random variable | Monte Carlo Simulation |
| Solicits opinions from experts, summarizes the opinions, and feeds the summaries back to the experts | Delphi Approach |
| Encourages the data itself to reveal its underlying structure rather than prematurely applying a hypothesis or statistical method | Exploratory Data Analysis (EDA) |
| Monitors the status of any process subject to acceptable or unacceptable variations during repeated operations | Statistical Control Charts |
| The cause-and-effect diagram. Useful for studying causation | Fishbone Diagram |
| The information system that supports routine process in an organization | Transaction processing system (TPS) |
| The term for determining how groups of data items in a relational structure are arranged in records in a database. | Normalization |
| Typically produce production report, pro forma FS, budgets, CVP analysis and other internal reports | MRS |
| Governance system components designed for a given purpose or context in a focus area. | Variant component |
| The acquisition of data that have already been created by control system within the organization | Signal reception |
| The final step before placing the system in live operation | User acceptance |
| Identifies the number of tests needed to get the coverage developers want | Combinatorial test design |
| Includes creating the system module by module until completed | Rapid application development techniques |