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| Section | Weight | Objectives |
|---|---|---|
| Data Governance, Quality, and Management | 14% | - Data lifecycle management and documentation - Data privacy, security, and compliance - Data governance frameworks and policies - Data quality standards and monitoring |
| Data Concepts and Environments | 20% | - Foundational concepts of AI and machine learning in data - Cloud and distributed data environments - Data types, structures, and formats - Database systems and architectures |
| Data Acquisition and Preparation | 22% | - Data extraction, transformation, and loading (ETL/ELT) - Data collection methods and sources - Data integration and normalization - Data cleaning, validation, and quality improvement |
| Visualization and Reporting | 20% | - Communicating insights to stakeholders - Validation and accuracy of reports - Dashboard and report development - Design principles for effective visualizations |
| Data Analysis | 24% | - Data modeling and pattern recognition - Statistical methods and techniques - Exploratory and confirmatory data analysis - Analytical tools and querying languages |
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NEW QUESTION # 204
A data analyst is gathering data from multiple tables in a database. The analyst needs certain columns from each table. Which of the following is the best method to accomplish this task?
Answer: C
Explanation:
A join combines data from multiple tables based on related fields, allowing the analyst to select specific columns from each table in a single result set.
NEW QUESTION # 205
The director of operations at a power company needs data to help identify where company resources should be allocated in order to monitor activity for outages and restoration of power in the entire state. Specifically, the director wants to see the following:
* County outages
* Status
* Overall trend of outages
INSTRUCTIONS:
Please, select each visualization to fit the appropriate space on the dashboard and choose an appropriate color scheme. Once you have selected all visualizations, please, select the appropriate titles and labels, if applicable.
Titles and labels may be used more than once.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
Answer:
Explanation:
Power outages
Explanation:
This is a simulation question that requires you to create a dashboard with visualizations that meet the director' s needs. Here are the steps to complete the task:
* Drag and drop the visualization that shows the county outages on the top left space of the dashboard.
This visualization is a map of the state with different colors indicating the number of outages in each county. You can choose any color scheme that suits your preference, but make sure that the colors are consistent and clear. For example, you can use a gradient of red to show the counties with more outages and green to show the counties with less outages.
* Drag and drop the visualization that shows the status of the outages on the top right space of the dashboard. This visualization is a pie chart that shows the percentage of outages that are active, restored, or pending. You can choose any color scheme that suits your preference, but make sure that the colors are distinct and easy to identify. For example, you can use red for active, green for restored, and yellow for pending.
* Drag and drop the visualization that shows the overall trend of outages on the bottom space of the dashboard. This visualization is a line graph that shows the number of outages over time. You can choose any color scheme that suits your preference, but make sure that the color is visible and contrasted with the background. For example, you can use blue for the line and white for the background.
* Select appropriate titles and labels for each visualization. Titles and labels may be used more than once.
For example, you can use "County Outages" as the title for the map, "Status" as the title for the pie chart, and "Trend" as the title for the line graph. You can also use "County", "Number of Outages",
"Active", "Restored", "Pending", "Time", and "Number of Outages" as labels for the axes and legends of the visualizations.
NEW QUESTION # 206
A data analyst is creating a report about cars sold within the last twelve months. The current data set only contains information from the last ten months. Which of the following is the most appropriate way to accomplish this task?
Answer: D
Explanation:
Extracting the missing records from the previous year and appending them ensures the dataset includes the full twelve-month period required for accurate reporting.
NEW QUESTION # 207
A sales manager wants a dashboard that shows sales aggregated by region and identifies high- volume sales by salesperson per region. Which of the following communication techniques best displays this information?
Answer: B
Explanation:
Level of detail allows data to be aggregated at different granularities, enabling analysis by region while also identifying high-volume sales at the salesperson level within each region.
NEW QUESTION # 208
A data analyst wants to analyze sales data for possible customer patterns. Which of the following should the analyst use to complete this task?
Answer: B
Explanation:
Clustering is a data analysis technique that groups customers or transactions with similar characteristics. By identifying these natural groupings within sales data, the analyst can discover customer patterns, behaviors, and trends that may not be immediately apparent.
NEW QUESTION # 209
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