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| Section | Objectives |
|---|---|
| Topic 1: Oracle Analytics Cloud Overview | - Architecture and service components - Core concepts of Oracle Analytics Cloud |
| Topic 2: Semantic Modeling and Data Modeling | - Metadata management - Subject areas and logical modeling |
| Topic 3: Data Preparation and Data Integration | - Data connections and sources - Data flows and pipelines - Data wrangling and transformation |
| Topic 4: Advanced Analytics and Machine Learning | - Predictive analysis and advanced insights - Machine learning capabilities in Oracle Analytics |
| Topic 5: Data Visualization and Reporting | - Filters, prompts, and interactive analysis - Creating dashboards and visualizations |
| Topic 6: Administration and Security | - Security configuration - User management and roles - Service administration |
1. Which two statements are true regarding the ways in which Oracle Analytics Cloud provides self-service data preparation capabilities?
A) Data sources can include application tables, data warehouses, data lake reservoirs, delimited flat files, and Microsoft Excel spreadsheets in the .xlsx format.
B) Join rules formashing up data from relational sources and delimited flat files can only be defined within the Oracle Analytics Cloud Data Modeler.
C) Data flows within the data preparation feature of Data Visualization can be used to extract, wrangle, and format data content from all supported data sources to create data sets upon which visuals may be constructed.
D) The Oracle Data Integrator tool used for extraction, load, and transformation of data is a foundational component of the Oracle Analytics Cloud and is essential for data preparation.
2. You've created an instance with 1 OCPU and 15 GB of RAM. What is this combination of OCPU and RAM called?
A) Compute shape
B) Classic compute
C) Analytics shape
D) Architecture shape
3. What does a confusion matrix illustrate?
A) a table that reports the occurrences of negative positives, false negatives, true positives, and positive negatives for a machine learning model
B) a table that reports the occurrences of higher positives, false negatives, lower positives, and true negatives for a machine learning model
C) a table that reports the occurrences of false positives, false negatives, true positives, and true negatives for a machine learning model
D) a table that reports the occurrences of upper positives, lower negatives, mid positives, and true negatives for a machine learning model
4. How can Oracle Analytics Cloud be used to visualize group relationships between data points on aparticular canvas?
A) Visualize the data by using a networkchart.
B) Use a variety of colors for each data point.
C) Create a cluster with a suitable number of groups for the specific analysis.
D) Use a combination of a tree diagram and a trellis visualization.
5. What statement is false regarding how Data Flow Sequences can beconfigured?
A) Sequences can be configured to fork multiple Data Flows to be run in parallel so as to complete data preparation more quickly than running flows serially.
B) To remove an item from a Sequence, click the Action menu icon at the far right of the line upon which the item is found and then select Remove from the drop-down menu,
C) Data Set prepare execution can be encapsulated by embedding Sequences inside of other Sequences.
D) To change the order of an item in the Sequence, the item can be selected by clicking it and dragging it up or down. It will be placed immediately below the highlighted item.
Solutions:
| Question # 1 Answer: A,C | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: A |
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