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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Mining | 25% | - Querying and retrieving data - Data profiling, cleansing, and validation - Data acquisition and integration methods - Data transformation, manipulation, and enrichment |
| Topic 2: Data Concepts and Environments | 15% | - Data types, structures, and formats - Structured, semi-structured, and unstructured data - Data storage systems: databases, data marts, warehouses, data lakes - Data schemas, dimensions, and attributes |
| Topic 3: Data Analysis | 23% | - Statistical methods: correlation, regression, hypothesis testing - Descriptive and inferential statistics - Interpreting results and identifying patterns/anomalies - Analytical techniques: trend, performance, exploratory, comparative |
| Topic 4: Data Governance, Quality and Controls | 14% | - Data quality standards and measurement - Data governance frameworks and policies - Data lifecycle management and controls - Data privacy, security, and compliance |
| Topic 5: Visualization and Reporting | 23% | - Building dashboards and reports - Selecting appropriate visualizations and charts - Design principles and best practices - Communicating insights and recommendations |
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問題 #90
A data analyst needs to perform a full outer join of a customer's orders using the tables below:
Which of the following is the mean of the order quantity?
答案：D
解題說明：
The correct answer is D. OUTER JOIN, seven rows.
An OUTER JOIN is a type of SQL join that returns all the rows from both tables, regardless of whether there is a match or not. If there is no match, the missing side will have null values. An OUTER JOIN can be either a LEFT JOIN, a RIGHT JOIN, or a FULL JOIN, depending on which table's rows are preserved1 Using the example tables, a FULL OUTER JOIN query would look like this:
SELECT Cust_id, Order_id, Order_qty FROM Sales_table FULL OUTER JOIN Order_table ON Sales_table.Order_id = Order_table.Order_id; The result of this query would be:
Cust_id | Order_id | Order_qty --------±---------±--------- 1 | 1 | 100 2 | 2 | 50 3 | 3 | 25 4 | 4 | 75 NULL | 5 | 10 NULL | 6 | 20 NULL | 7 | 15 As you can see, the query returns seven rows, one for each order in either table. The orders that are not in the Sales_table have null values for the Cust_id column.
To find the mean of the order quantity, we need to sum up the order quantities and divide by the number of rows. In this case, the mean is (100 + 50 + 25 + 75 + 10 + 20 + 15) / 7 = 42.14. Rounding to one decimal place, we get 42.1 as the mean of the order quantity.
問題 #91
A data analyst is developing a data dictionary that aligns with a company's data management processes and policies. Which of the following best describes what should be included in the data dictionary?
答案：D
問題 #92
What category of data stewardship work is focused on ensuring that the organization respects the wishes of data subjects?
答案：D
問題 #93
What effort has the goal of maintaining a single source of truth for the most important data elements handled by the organization?
答案：D
解題說明：
Master data management (MDM) involves creating a single master record for each person, place, or thing in a business, from across internal and external data sources and applications. This information has been de-duplicated, reconciled and enriched, becoming a consistent, reliable source. Once created, this master data serves as a trusted view of business-critical data that can be managed and shared across the business to promote accurate reporting, reduce data errors, remove redundancy, and help workers make better-informed business decisions.
問題 #94
A data analyst is compiling a report that a Chief Executive Officer needs for an impromptu meeting. The report should include information on the previous day's performance. Which of the following reports should the analyst provide?
答案：D
問題 #95
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