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| Section | Weight | Objectives |
|---|---|---|
| Securing Data | 8% | - Data governance policies - Secure storage and compliance - Access control and permissions |
| Creating Dashboards and Visualizations in Databricks | 16% | - Visualization types and best practices - Filtering and interactivity - Scheduling and sharing dashboards - Dashboard creation and layout |
| Developing, Sharing, and Maintaining AI/BI Genie Spaces | 12% | - Maintenance and improvement - Natural language query setup - Access control and sharing - Genie space setup and configuration |
| Executing Queries using Databricks SQL and Databricks SQL Warehouses | 20% | - Warehouse configuration and performance - Aggregations and grouping - Creating and managing views - Joining and combining datasets - ANSI SQL syntax and functions |
| Data Modeling with Databricks SQL | 5% | - Performance-oriented modeling - Schema design principles - Delta table structure |
| Importing Data | 5% | - UI-based data ingestion - API and Auto Loader - S3 and cloud storage integration - Databricks Marketplace - Delta Sharing |
| Analyzing Queries | 15% | - Liquid clustering and indexing - Performance optimization - Execution plans and analysis - Query history and auditing |
| Managing Data | 8% | - Discovering and registering datasets - Data cleaning and preparation - Unity Catalog usage - Dataset versioning and management |
| Understanding of Databricks Data Intelligence Platform | 11% | - Workspace navigation and interface - Core architecture and components - Lakehouse platform fundamentals |
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NEW QUESTION # 102
Which of the following statements describes descriptive statistics?
Answer: D
Explanation:
Descriptive statistics is a branch of statistics that uses summary statistics, such as mean, median, mode, standard deviation, range, frequency, or correlation, to quantitatively describe and summarize data. Descriptive statistics can help data analysts understand the main features of a data set, such as its central tendency, variability, or distribution. Descriptive statistics can also help data analysts visualize data using charts, graphs, or tables. Descriptive statistics do not make any inferences or predictions about the data, unlike inferential statistics, which use data analysis techniques to infer properties of an underlying population or probability distribution from a sample of data. Reference: Databricks - Descriptive Statistics, Databricks - Data Analysis with Databricks SQL
NEW QUESTION # 103
A data scientist has asked a data analyst to create histograms for every continuous variable in a data set. The data analyst needs to identify which columns are continuous in the data set.
What describes a continuous variable?
Answer: C
Explanation:
A continuous variable is a type of quantitative variable that can assume an infinite number of values within a given range. This means that between any two possible values, there can be an infinite number of other values. For example, variables such as height, weight, and temperature are continuous because they can be measured to any level of precision, and there are no gaps between possible values. This is in contrast to discrete variables, which can only take on specific, distinct values (e.g., the number of children in a family).
Understanding the nature of continuous variables is crucial for data analysts, especially when selecting appropriate statistical methods and visualizations, such as histograms, to accurately represent and analyze the data.
NEW QUESTION # 104
Which of the following is a benefit of Databricks SQL using ANSI SQL as its standard SQL dialect?
Answer: A
Explanation:
Databricks SQL uses ANSI SQL as its standard SQL dialect, which means it follows the SQL specifications defined by the American National Standards Institute (ANSI). This makes it easier to migrate existing SQL queries from other data warehouses or platforms that also use ANSI SQL or a similar dialect, such as PostgreSQL, Oracle, or Teradata. By using ANSI SQL, Databricks SQL avoids surprises in behavior or unfamiliar syntax that may arise from using a non-standard SQL dialect, such as Spark SQL or Hive SQL12. Moreover, Databricks SQL also adds compatibility features to support common SQL constructs that are widely used in other data warehouses, such as QUALIFY, FILTER, and user-defined functions2. Reference: ANSI compliance in Databricks Runtime, Evolution of the SQL language at Databricks: ANSI standard by default and easier migrations from data warehouses
NEW QUESTION # 105
A data analyst is working with a nested array column products in table transactions. The analyst wants to return the first item in the array for each row.
The data analyst is using the following incomplete command:
SELECT
transaction_id,
_____ AS first_product
FROM transactions;
Which line of code should the data analyst use to fill in the blank so that it successfully completes the task?
Answer: A
Explanation:
The correct answer is C because Databricks SQL supports bracket notation for arrays, and array indexing starts at 0. Therefore, the first element of the products array is accessed with products[0]. Options A and B use dot notation, which is not the correct syntax for array indexing. Option D returns the second element, not the first.
Official documentation extract used: Databricks states that the bracket operator returns an array element by index and that "the first element of an ARRAY is at index 0."
NEW QUESTION # 106
A data analyst created and is the owner of the managed table my_ table. They now want to change ownership of the table to a single other user using Data Explorer.
Which of the following approaches can the analyst use to complete the task?
Answer: C
Explanation:
The Owner field in the table page shows the current owner of the table and allows the owner to change it to another user or group. To change the ownership of the table, the owner can click on the Owner field and select the new owner from the drop-down list. This will transfer the ownership of the table to the selected user or group and remove the previous owner from the list of table access control entries1. The other options are incorrect because:
A . Removing the owner's account from the Owner field will not change the ownership of the table, but will make the table ownerless2.
B . Selecting All Users from the Owner field will not change the ownership of the table, but will grant all users access to the table3.
D . Selecting the Admins group from the Owner field will not change the ownership of the table, but will grant the Admins group access to the table3.
E . Removing all access from the Owner field will not change the ownership of the table, but will revoke all access to the table4. Reference:
1: Change table ownership
2: Ownerless tables
3: Table access control
4: Revoke access to a table
NEW QUESTION # 107
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