1z0-1195-25 Sample Questions Answers

Oracle’s Data Management strategy aims to deliver "the fastest, most scalable converged SQL database" (A), exemplified by its Autonomous Database and Exadata systems, which support multiple data types and workloads efficiently. It also seeks to "automate everything for developers, data analysts, DBAs, and data scientists" (B), leveraging self-managing, self-tuning capabilities to reduce manual effort and enhance productivity. Option C ("multiple integration points for 3rd party databases") is not a primary objective, as Oracle focuses on its own ecosystem. Option D ("best platform for warehouse workloads only") is too narrow, as the strategy spans beyond just warehousing to include transactional, analytical, and JSON workloads. Oracle’s official data management documentation emphasizes speed, scalability, and automation as core goals.

The "built-in SQL Worksheet and Notebook" (e.g., in Autonomous Database’s Database Actions) have two true statements: "No need to install a client query tool" (C), as it’s web-based and accessible via browser, and "Quickly start running queries with built-in web-based notebooks" (D), enabling immediate SQL execution. "Based on Apache Tomcat" (A) is not specified in documentation, and "Need to install client query tool for the PL/SQL" (B) is false due to its integrated nature. Oracle’s documentation confirms these web-based features.

The Exadata X8M leverages "Remote Direct Memory Access" (RDMA) to access "Persistent Memory" (B). RDMA allows direct memory-to-memory data transfer between systems without CPU involvement, enhancing performance. In Exadata X8M, RDMA accesses persistent memory (PMEM) to accelerate database operations by reducing latency and improving I/O throughput. "Compute Instances" (A) and "Database Servers" (D) are broader entities, not the specific resource RDMA targets, while "Storage Disks" (C) are traditional storage, not memory. Oracle’s Exadata documentation highlights RDMA’s use with persistent memory in X8M systems.

"FastConnect" (D) is the interconnect solution to connect Oracle Cloud Infrastructure (OCI) to other cloud providers (e.g., Azure, AWS) via dedicated, high-speed links. "Virtual Cloud Network" (A) is an OCI internal network, "Virtual Private Cloud" (B) is an AWS term, and "Cloud Router" (C) is not a specific OCI offering (though third-party routers like Megaport exist). Oracle’s documentation confirms FastConnect for multicloud connectivity.

An example of an in-database option in Oracle Automated Machine Learning (AutoML) is "Oracle Machine Learning for Python (OML4PY) APIs" (C). OML4Py enables Python-based machine learning directly within the database, leveraging in-database algorithms for performance and security. "REST Interface" (A) is an access method, "Cognitive text" (B) is a feature, not an algorithm type, and "Tuning of hyperparameter" (D) is a process, not a specific option. Oracle’s documentation highlights OML4Py as a key in-database ML tool.

The "MySQL Database Service" on OCI uses "Block Volume Storage" (D) for all data storage, providing high-performance, persistent block storage attached to compute instances for database operations. "Object Storage" (A) is for unstructured data, "Flash Local Storage" (B) is temporary and instance-specific, and "File Storage" (C) is for shared file systems—none suit MySQL’s needs. Oracle’s MySQL Service documentation confirms Block Volume as the standard.

A prerequisite for running "APEX" (Application Express) on an Autonomous Database is provisioning "an Autonomous Database with the workload type Data Warehouse, TransactionProcessing, JSON, or APEX" (B). APEX is supported across these workload types, with ORDS (Oracle REST Data Services) pre-enabled. Option A is incorrect, as ORDS is automatically configured. Option C is too restrictive, as APEX isn’t limited to the APEX workload type alone. Option D is unnecessary, as user creation follows provisioning, not precedes it. Oracle’s Autonomous Database documentation confirms APEX availability across these workload types with no manual ORDS setup required.

"Compartments" (B) in Oracle Cloud Infrastructure (OCI) allow you to logically group and isolate resources for organization, access control, and billing. "Identity and Access Management Groups" (A) organize users, not resources. "Tenancy" (C) is the root container for all resources, not a grouping mechanism, and "Availability Domain" (D) is a physical data center division, not a logical grouping tool. Oracle’s OCI documentation identifies Compartments as the primary feature for resource isolation and management.

Full Detailed In-Depth Explanation: Oracle APEX (Application Express) is a leading low-code platform designed to simplify and accelerate application development, particularly within the Oracle ecosystem. The two main features of APEX’s low-code platform are "Use graphical user interfaces and configuration" (D) and "Focus on business requirements" (F). Option D reflects APEX’s core strength: it provides a browser-based, declarative development environment with drag-and-drop functionality, wizards, and visual UI tools, allowing developers and business users to build applications with minimal coding. This reduces complexity and speeds up development, aligning with the low-code philosophy. Option F highlights APEX’s emphasis on enabling users to address business needs directly, rather than getting bogged down in technical intricacies, by offering prebuilt components and templates tailored to solve real-world problems efficiently. "Limited productivity" (A) is incorrect, as APEX enhances productivity significantly. "Build scalable web apps for MongoDB" (B) is false, as APEX is optimized for Oracle Database, not MongoDB. "Simplified core-based licensing" (C) is a licensing aspect, not a development feature, and "Use traditional computer programming paradigms" (E) contradicts APEX’s low-code approach, which minimizes hand-coding. Oracle’s official APEX documentation emphasizes its graphical, business-focused design as key differentiators.

In OCI Identity and Access Management (IAM), "Groups" (A) is the capability that helps organize multiple users into teams. Groups allow administrators to assign permissions collectively to a set of users, simplifying access management. "Policies" (B) define permissions but don’t organize users, "Users" (C) are individual accounts, and "Roles" (D) are not a distinct IAM construct in OCI (unlike other clouds). Oracle’s IAM documentation identifies Groups as the mechanism for team-based organization.

In the Oracle Cloud Infrastructure (OCI) Lakehouse, data processing capabilities are provided by services designed to handle computation and transformation of data. "Autonomous Database" (A) offers self-managing data processing for SQL workloads, "Big Data Service" (C) supports large-scale processing with Hadoop and Spark, and "OCI Data Flow" (D) enables serverless Spark processing. However, "NoSQL Service" (B) is primarily a storage service for unstructured key-value data, optimized for high-performance retrieval and scalability, not for general data processing tasks like transformation or analytics. Oracle’s Lakehouse documentation emphasizes processing services like Autonomous Database, Big Data Service, and OCI Data Flow, while NoSQL Service is positioned for persistence and access rather than processing.

The Oracle-recommended way to upgrade databases is "AutoUpgrade" (D). AutoUpgrade automates the upgrade process, handling pre-checks, upgrades, and post-upgrade tasks with minimal manual intervention, reducing errors and downtime. "Database Upgrade Assistant (DBUA)" (A) is a GUI tool but less automated, "Data Pump Export/Import" (B) is for data migration, not direct upgrades, and "Command Line Upgrade" (C) is manual and error-prone. Oracle’s official upgrade guides endorse AutoUpgrade for its efficiency and reliability.

In the Autonomous Database (ADB), "Data Insights" (B) is the tool to discover anomalies, outliers, and hidden patterns, leveraging built-in AI and ML capabilities to analyze data. "Data Load" (A) is for importing data, "Data Transforms" (C) is for data preparation, and "Catalog" (D) is for metadata (OCI Data Catalog). Oracle’s documentation identifies Data Insights for pattern detection.

When provisioning an "Autonomous Database" on Oracle Cloud Infrastructure, the supported workload types include "JSON" (B) for document-centric applications, "Data Warehouse" (C) for analytics, and "APEX" (D) for low-code application development, alongside Transaction Processing (not listed here). "MySQL" (A) is not a workload type for Autonomous Database; instead, it is a separate database service (Oracle MySQL Database Service) on OCI, not part of the Autonomous Database offering. Oracle’s documentation specifies the distinct workload options available during Autonomous Database provisioning, excluding MySQL.

In a simple cloud management model (e.g., Autonomous Database), "Manage database servers and VM hosts" (A) is not the customer’s responsibility; Oracle handles infrastructure management.Customers "Subscribe to database servers" (B), manage "Everything inside of the database" (C) like data and schemas, and "Control access to customer VMs" (D) where applicable. Oracle’s shared responsibility model delegates server and host management to the provider.