_________ in data governance refers to the policies and processes ensuring data integrity and security.
- Data Management
- Data Privacy
- Data Quality
- Data Stewardship
Data Stewardship in data governance refers to the policies and processes ensuring data integrity and security. It involves the responsible management and oversight of data to maintain its quality and protect its confidentiality and integrity.
In ETL processes, what does the acronym ETL stand for?
- Evaluate, Transform, Load
- Extract, Transfer, Load
- Extract, Transform, Load
- Extract, Translate, Load
ETL stands for Extract, Transform, Load. This process involves extracting data from various sources, transforming it to meet business requirements, and loading it into a target system for analysis.
In a healthcare setting, what performance metric would be most suitable for assessing patient care quality?
- Employee Turnover Rate
- Number of Appointments Scheduled
- Patient Satisfaction Score
- Revenue per Patient
Patient Satisfaction Score is a crucial metric for assessing patient care quality in a healthcare setting. It reflects the overall satisfaction of patients with the care they received, including factors like communication, empathy, and overall experience.
For a project involving geospatial data, which R package provides comprehensive tools for handling spatial data?
- dplyr
- ggplot2
- leaflet
- rgdal
The rgdal package in R is designed for handling geospatial data. It provides functions for reading and writing spatial data in various formats, making it a comprehensive tool for projects involving geospatial analysis.
When presenting a data-driven story to a non-technical audience, what type of visualization should be prioritized to enhance understanding and engagement?
- 3D Charts
- Box Plots
- Histograms
- Infographics
Infographics are ideal for presenting data to a non-technical audience as they combine visuals and text to convey information in a clear and engaging manner. 3D Charts, Histograms, and Box Plots may be too technical or less intuitive for a non-technical audience.
What data structure is used to implement Depth First Search (DFS) on a graph?
- Array
- Linked List
- Queue
- Stack
Depth First Search (DFS) is typically implemented using a stack data structure. This is because DFS explores as far as possible along each branch before backtracking, which aligns well with the Last In, First Out (LIFO) nature of a stack.
Which SQL command is used to retrieve data from a database table?
- DELETE
- INSERT
- SELECT
- UPDATE
The SQL command used to retrieve data from a database table is SELECT. It allows you to query and fetch specific data based on specified conditions. UPDATE, DELETE, and INSERT are used for modifying or adding data.
What is the primary difference between an integer and a float data type in most programming languages?
- Integer and Float are the same data type.
- Integer can store larger values than Float.
- Integer is used for text data, while Float is used for numeric data.
- Integer stores whole numbers without decimals, while Float stores numbers with decimals.
The primary difference is that Integer stores whole numbers without decimals, while Float stores numbers with decimals. Integer and Float are both used for numeric data.
In advanced Excel, what method would you use to import and transform data from an external database?
- Advanced Filter
- Data Consolidation
- Data Validation
- Power Query
Power Query is the method used in advanced Excel to import and transform data from an external database. It provides a user-friendly interface to connect, import, and transform data seamlessly. Data Validation, Advanced Filter, and Data Consolidation are not specifically designed for importing and transforming external database data.
The process of estimating the parameters of a probability distribution based on observed data is known as _______.
- Bayesian Inference
- Hypothesis Testing
- Maximum Likelihood Estimation
- Regression Analysis
Maximum Likelihood Estimation (MLE) is the process of finding the values of parameters that maximize the likelihood of observed data. It's a fundamental concept in statistics for parameter estimation.