Jpshikenの1Z0-931-26模擬テストに関する限り、PDFバージョンは次の2つの側面に関して非常に便利です。 一方、PDFバージョンには、1Z0-931-26テストトレントの全バージョンから選択された質問の一部が含まれているデモが含まれています。 このようにして、実際の準備試験の一般的な理解を得ることができます。これは、適切な試験ファイルの選択に役立つはずです。 一方、Oracle Autonomous AI Database Professionalの1Z0-931-26準備資料を印刷して、Oracle論文とPDF版で試験の勉強をすることができます。 このようなメリットがあるので、試してみませんか？
| Section | Weight | Objectives |
|---|---|---|
| Applying Autonomous Database Serverless Architectures | - Configure Autonomous Database Serverless environments - Implement connectivity and access methods - Manage compute resources and auto scaling | |
| Implementing Autonomous Database Dedicated Deployments | 20% | - Manage dedicated deployment resources - Configure Autonomous Database Dedicated Infrastructure - Apply security and isolation features |
| Migration and Data Integration Strategies | - Use data integration and migration tools - Plan and execute database migration strategies | |
| Managing, Monitoring, and Optimizing Autonomous Database Performance | 20% | - Optimize workloads and database performance - Manage backup, recovery, and availability features - Monitor database performance and resource usage |
| Using Autonomous Database Tools | - Use Oracle Database tools and management interfaces - Use Oracle APEX and Oracle Machine Learning with Autonomous Database | |
| Designing Unified Data Management and AI Analytics Solutions | - Use data sharing and integration features - Implement JSON, graph, spatial, and text data capabilities - Apply analytics and AI-driven data solutions | |
| Applying Select AI Capabilities | - Configure and use Select AI features - Use natural language queries with generative AI capabilities | |
| Implementing Model Context Protocol (MCP) Server Integration | - Understand MCP Server integration concepts - Integrate AI applications with Autonomous Database services | |
| Implementing Autonomous Database Fundamentals | - Understand Autonomous Database automation capabilities - Provision and configure Autonomous Database services - Describe Autonomous Database architecture and key features |
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質問 # 60
You have been tasked with analyzing a year’s worth of sales data stored in an Autonomous Data Warehouse instance. Which tool would you use to automate data exploration and create pivot tables?
正解：D
解説：
Full Detailed In-Depth Explanation:
A: False. APEX is for app development, not data exploration.
B: False. SQL Developer Web is for SQL queries, not pivot tables.
C: True. Business Models in ADW automates data exploration and generates pivot tables.
D: False. Data Load is for importing data, not analysis.
質問 # 61
Which predefined service connection should you use when running lots of high concurrent queries in an Autonomous Database?
正解：B
解説：
Full Detailed In-Depth Explanation:
Service connections in Autonomous Database:
A . DBNAME_LOW: Optimized for high concurrency with minimal resources per query, ideal for many simultaneous queries.
B . DBNAME_MEDIUM: Balanced concurrency and performance.
C . DBNAME_HIGH: Prioritizes individual query performance, not concurrency.
D . DBNAME_CONCURRENT: Not a valid service name.
質問 # 62
Which three methods can be used to migrate your existing Oracle database to Autonomous Database? (Choose three.)
正解：A、B、D
解説：
Migrating to Autonomous Database requires robust tools:
Correct Answer (B): Oracle Zero Downtime Migration (ZDM) minimizes downtime by synchronizing data and schema changes while the source remains online, ideal for critical systems.
Correct Answer (C): GoldenGate provides real-time replication, enabling near-zero downtime migration by continuously syncing data to Autonomous Database.
Correct Answer (D): Data Pump exports data and schema to dump files, which are then imported into Autonomous Database, suitable for offline migrations.
Incorrect Options:
A: SFTP with CSV files is not a comprehensive migration method; it lacks schema migration and automation for complex databases.
E: RMAN is for backup/restore, not optimized for full migrations to Autonomous Database’s managed environment.
These methods cater to different migration needs (online vs. offline).
質問 # 63
Which statement is true about connecting a marketplace Oracle Cloud Infrastructure (OCI) image to an Autonomous Database on Shared Infrastructure?
正解：A
質問 # 64
Which two optimizations are different between Autonomous Data Warehouse and Autonomous Transaction Processing? (Choose two.)
正解：A、C
解説：
Autonomous Data Warehouse (ADW) and Autonomous Transaction Processing (ATP) are optimized for different workloads, reflected in their configurations. The two differing optimizations are:
Memory Usage (A): ADW and ATP allocate memory differently to suit their purposes. ADW prioritizes a larger data cache (part of the SGA) to keep more data in memory, boosting analytical query performance (e.g., aggregations over millions of rows). For example, a SELECT SUM(sales) GROUP BY region runs faster with more cached data. ATP, conversely, balances memory across the SGA and PGA for transactional workloads, emphasizing concurrency and quick row-level operations (e.g., UPDATE orders SET status = 'shipped'). This difference ensures ADW excels at scan-heavy analytics, while ATP handles high-throughput updates.
Data Organization (B): ADW uses a columnar storage format (e.g., Hybrid Columnar Compression) optimized for analytics, storing data by column to speed up aggregations and reduce I/O (e.g., scanning only the sales column for a SUM). ATP uses a row-based format suited for OLTP, enabling fast single-row access and updates (e.g., retrieving or modifying a specific order_id). For instance, inserting a row in ATP is efficient due to row storage, while ADW’s columnar format accelerates SELECT AVG(price) FROM products.
The incorrect options are:
Backup Retention (C): Both ADW and ATP use the same automatic backup system (via Oracle’s Automatic Workload Repository), with a default 60-day retention adjustable by users. There’s no optimization difference here; it’s a shared managed feature.
Undo Management (D): Both databases use Oracle’s Flashback technology for undo (e.g., rolling back transactions or querying past states), with retention periods set similarly. Undo is managed automatically in both, not optimized differently.
These optimizations tailor ADW for analytics and ATP for transactions, despite their shared autonomous foundation.
質問 # 65
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