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| Section | Weight | Objectives |
|---|---|---|
| Managing and Securing Oracle Analytics Publisher in Oracle Analytics Cloud | 10% | |
| Managing Report Scheduling, Data Sources, Administration, and Translations in Oracle Analytics Publisher | 15% | |
| Understanding Oracle Analytics Cloud | 5% | |
| Formatting Data and Managing Filters, Selection Steps, and Variables in Oracle Analytics | 10% | |
| Designing, Creating, and Enhancing Dashboards in Oracle Analytics | 10% | |
| Exploring and Creating Reports and Data Models in Oracle Analytics Publisher | 5% | |
| Managing Administration, Security, and Performance in Oracle Analytics Cloud | 10% | |
| Connecting to Data Sources and Migrating Artifacts to Oracle Analytics Cloud | 10% | |
| Managing and Creating Analyses, Views, and Content in Oracle Analytics | 10% | |
| Building and Formatting Reports Using Layout Editor and Template Builder | 15% |
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NEW QUESTION # 37
A report needs to group Revenue values by item type and Per-Year-Month into four dynamic buckets and may need to return the bin names. Which function should the author use?
Answer: E
Explanation:
The BIN function is specifically designed to classify a numeric expression into a defined number of equal- width buckets. Oracle documents syntax in which a numeric expression is evaluated at a specified grain using the BY clause, followed by INTO n BINS. The function can return the bin number or one of the interval boundary values , making it appropriate when the analysis needs both dynamic bucketing and a usable representation of each bucket.
In this scenario, Revenue is the numeric measure, while item type and Per-Year-Month establish the required analytical grain. Specifying four bins therefore partitions Revenue values into four dynamically calculated ranges at that grain.
MSUM calculates a moving sum across rows; it doesn't classify values into buckets. PERIODROLLING performs time-series aggregation over a specified period. RANK returns relative ordering, while TOPN identifies the highest-ranked members. None of these functions creates equal-width numeric bins.
Therefore, BIN applied to Revenue at the required grain and configured for four bins directly satisfies the requirement. Oracle's function reference explicitly defines BIN for this purpose.
Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables - Analysis Functions and BIN
NEW QUESTION # 38
An author wants to combine results from two subject areas in an analysis and asks whether the Analysis Editor can create joins between subject areas. Which approach should the author use?
Answer: D
Explanation:
When the objective is to stack separate result sets , the Analysis Editor supports set operations such as UNION, UNION ALL, INTERSECT, and DIFFERENCE . Oracle documents a specific Combine Results function that lets authors create criteria from another subject area and apply a set operator to the two query result sets.
Set operations, however, aren't relational join definitions. They combine compatible result sets and require matching numbers of columns and compatible data types. They don't create primary-key/foreign-key or other semantic relationships between subject areas.
Cross-subject-area relational behavior depends on the semantic model , including common dimensions, facts, and relationships defined for the participating subject areas. Oracle also supports cross-subject-area analyses using conformed dimensions, but those relationships derive from model metadata rather than a join created ad hoc through set-operation syntax.
Dashboard prompts simply provide runtime filtering and don't create data relationships. Likewise, adding a second query doesn't itself define semantic join logic.
Therefore, the accurate distinction is: use set operators when stacking compatible result sets; define and govern actual joins through the semantic model .
Reference Topic: Managing and Creating Analyses, Views, and Content - Combining Subject Areas and Set Operations
NEW QUESTION # 39
Which type of report is an example of the bursting feature in Pixel-Perfect Reporting?
Answer: A
NEW QUESTION # 40
An administrator wants to minimize the impact of frequently executed analytical queries on the underlying database while maintaining acceptable response times. Which combination provides the best solution?
Answer: D
Explanation:
The most effective combination is query caching plus an optimized semantic model . Oracle Analytics query caching stores previously generated query results so that compatible subsequent requests can be satisfied without repeatedly executing equivalent SQL against the underlying database. This reduces database workload, network traffic, and analytical response time for frequently repeated requests.
Caching alone, however, is not a substitute for sound semantic-model design. Proper logical relationships, aggregation behavior, source mappings, calculations, and physical connection configurations influence the efficiency of generated queries. Optimizing the model therefore addresses the cost of queries that do reach the source, while caching prevents unnecessary repetition of previously resolved requests.
Oracle also emphasizes that administrators need an appropriate cache-management strategy. Cache entries must be invalidated when source data or semantic-model definitions change so that users don't receive stale results.
Disabling caching increases database load. Duplicate subject areas add administrative complexity without inherently improving performance. Running every analysis every minute can substantially increase processing rather than reduce it.
Therefore, C provides the correct performance architecture: optimize query generation and use caching to avoid unnecessary source executions.
Reference Topic: Managing Administration, Security, and Performance - Query Cache and Semantic Model Performance
NEW QUESTION # 41
An administrator is preparing Oracle Analytics Publisher to deliver scheduled reports to OCI Object Storage.
Which two requirements or setup actions support this delivery channel?
Answer: D,E
Explanation:
OCI Object Storage can be configured as an Oracle Analytics Publisher delivery destination, but the Publisher service requires both appropriate OCI permissions and authentication information.
First, the administrator must have access to an OCI compartment in which an Object Storage bucket can be created or used. Oracle documents specific tenancy and compartment permissions for this purpose, including access to the Object Storage namespace and required bucket/object operations.
Second, Oracle's documented configuration workflow instructs the administrator to use the OCI Console to create a bucket and configure an API key for authentication . The associated user, tenancy OCIDs, public- key fingerprint, private key, compartment, and bucket information are then used when defining the Object Storage delivery server in Publisher.
CUPS and fax4CUPS relate to printer/fax delivery rather than OCI Object Storage. An Intradoc URI and Content Server metadata concern Oracle WebCenter Content integration. SMTP is required for email delivery but not Object Storage.
Therefore, compartment/bucket access and an OCI bucket authenticated through an API signing-key configuration are the two prerequisites directly associated with this Publisher delivery channel.
Reference Topic: Managing Report Scheduling, Data Sources, Administration, and Translations - Object Storage Delivery
NEW QUESTION # 42
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