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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Governance, Quality and Controls | 14% | - Data privacy, security, and compliance - Data lifecycle management and controls - Data quality standards and measurement - Data governance frameworks and policies |
| Topic 2: Data Mining | 25% | - Data transformation, manipulation, and enrichment - Data profiling, cleansing, and validation - Data acquisition and integration methods - Querying and retrieving data |
| Topic 3: Data Concepts and Environments | 15% | - Data schemas, dimensions, and attributes - Data types, structures, and formats - Structured, semi-structured, and unstructured data - Data storage systems: databases, data marts, warehouses, data lakes |
| Topic 4: Data Analysis | 23% | - Analytical techniques: trend, performance, exploratory, comparative - Statistical methods: correlation, regression, hypothesis testing - Interpreting results and identifying patterns/anomalies - Descriptive and inferential statistics |
| Topic 5: Visualization and Reporting | 23% | - Selecting appropriate visualizations and charts - Design principles and best practices - Building dashboards and reports - Communicating insights and recommendations |
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NEW QUESTION # 142
What technique can you use to predict one value from another using a linear relationship?
Answer: A
NEW QUESTION # 143
Given the following customer and order tables:
Which of the following describes the number of rows and columns of data that would be present after performing an INNER JOIN of the tables?
Answer: B
Explanation:
This is because an INNER JOIN is a type of join that combines two tables based on a matching condition and returns only the rows that satisfy the condition. An INNER JOIN can be used to merge data from different tables that have a common column or a key, such as customer ID or order ID. To perform an INNER JOIN of the customer and order tables, we can use the following SQL statement:
This statement will select all the columns (*) from both tables and join them on the customer ID column, which is the common column between them. The result of this statement will be a new table that has seven rows and eight columns, as shown below:
The reason why there are seven rows and eight columns in the result table is because:
* There are seven rows because there are six customers and six orders in the original tables, but only five customers have matching orders based on the customer ID column. Therefore, only five rows will have data from both tables, while one row will have data only from the customer table (customer 5), and one row will have no data at all (null values).
* There are eight columns because there are four columns in each of the original tables, and all of them are selected and joined in the result table. Therefore, the result table will have four columns from the customer table (customer ID, first name, last name, and email) and four columns from the order table (order ID, order date, product, and quantity).
NEW QUESTION # 144
Refer to the exhibit.
Which of the following logical statements results in Table B?
Answer: C
Explanation:
The logical statement that results in Table B is Option D. Option D is a logical statement that uses the AND operator to combine two conditions: Name = "Tom" and Region = "BC". The AND operator returns true only if both conditions are true, otherwise it returns false. Therefore, Option D will select only the rows from Table A that satisfy both conditions, which are rows 4, 5, 6, and 7. These rows form Table B, as shown below:
Name | Gender flag | Level | College | Code | Region Tom | Male | Elementary | A | BC | BC Kim | Female | Elementary | A | BC | BC Pat | Female | Elementary | A | BC | BC Ben | Male | Elementary | A | BC | BC The other options are not correct, as they use different logical operators or conditions that do not result in Table B. Option A uses the OR operator, which returns true if either condition is true, or both. Option A will select all the rows from Table A except row 3, which does not match either condition. Option B uses the NOT operator, which returns the opposite of the condition. Option B will select all the rows from Table A except rows 4, 5, 6, and 7, which match the condition. Option C uses a different condition, Region = "ON", which does not match any row in Table A. Option C will select no rows from Table A. Reference: [SQL Logical Operators - W3Schools]
NEW QUESTION # 145
Given the following table:
Which of the following methods is the best way to describe the changes in the values in the table?
Answer: A
NEW QUESTION # 146
A data analyst wants to create "Income Categories" that would be calculated based on the existing variable
"Income". The "Income Categories" would be as follows:
Income category 1: less than $1.
Income category 2: more than $1 and less than $20,000.
Income category 3: more than $20,001 and less than $40,000.
Income category 4: more than $40,001.
Which of the following data manipulation techniques should the data analyst use to create "Income Categories"?
Answer: A
Explanation:
The correct answer is B: Derived variables Derived variables are variables that you create by calculating or categorizing variables that already exist in your data set.
Data merge is incorrect. Data merging is the process of combining two or more data sets into a single data set.
Data blending is incorrect.
Data blending involves pulling data from different sources and creating a single, unique, dataset for visualization and analysis.
Data append is incorrect. A data append is a process that involves adding new data elements to an existing database.
NEW QUESTION # 147
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