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Data Warehousing 11g Essentials

Question No: 31

Which feature would enable higher availability during maintenance operations while also improving query response performance?

  1. Partitioning

  2. Materialized views

  3. Bitmap Indexing

  4. OLAP

Answer: A

Explanation: Partitioning enhances the performance, manageability, and availability of a wide variety of applications and helps reduce the total cost of ownership for storing large amounts of data. Partitioning allows tables, indexes, and index-organized tables to be subdivided into smaller pieces, enabling these database objects to be managed and accessed at a finer level of granularity. Oracle provides a rich variety of partitioning strategies and extensions to address every business requirement. Moreover, since it is entirely transparent, partitioning can be applied to almost any application without the need for potentially expensive and time consuming application changes.

Reference: Oracle庐 Database VLDB and Partitioning Guide, 11g Release 1 (11.1), 2 Partitioning Concepts

Question No: 32

What two types of results can be cached in the Result Set Cache?

  1. Results of an SQL query

  2. Results from a PL/SQL function

  3. Sequence object results

  4. Result sets derived from data dictionary tables

Answer: A,B

Explanation: Your applications sometime send repetitive queries to the database. To improve the response time of repetitive queries, results of queries, query fragments, and PL/SQL functions can be cached in memory. A result cache stores the results of queries shared across all sessions. When these queries are executed repeatedly, the results are retrieved directly from the cache memory.

You must annotate a query or query fragment with a result cache hint to indicate that results are to be stored in the query result cache.

The query result set can be cached in the following ways:

  • Server-side Cache

  • Client Result Cache

    Oracle Database 11g Release 1 (11.1) provides support for server-side Result Set caching for both JDBC types. The server-side result cache is used to cache the results of the current queries, query fragments, and PL/SQL functions in memory and then to use the cached results in future executions of the query, query fragment, or PL/SQL function. The cached results reside in the result cache memory portion of the SGA. A cached result is automatically invalidated whenever a database object used in its creation is successfully modified. The server-side caching can be of the following two types:

  • SQL Query Result Cache (A)

  • PL/SQL Function Result Cache (B)

Question No: 33

Knowledge Modules are:

  1. Reusable code templates for Oracle Data Integrator

  2. Prebuilt applications for Oracle Business Intelligence

  3. Options for Oracle Enterprise Manager

  4. Algorithms for data mining

Answer: A

Explanation: Knowledge modules (KMs) in Oracle Data Integrator are components that implement reusable transformation and ELT (extract, load, and transform) strategies across different technologies.

Reference: Developing a Knowledge Module in Oracle Data Integrator

http://www.oracle.com/technetwork/articles/bethke-odi-090881.html

Question No: 34

Which Oracle option might be used to encrypt sensitive data in an Oracle data warehouse?

  1. Active Data Guard

  2. Total Recall

  3. Advanced Security Option

  4. Virtual Private Database

Answer: C

Explanation: Oracle Advanced Security is an option to the Oracle Database 11g Enterprise

Edition that helps address privacy and regulatory requirements including the Payment Card Industry Data Security Standard (PCI-DSS), Health Insurance Portability and Accountability Act (HIPAA), and numerous breach notification

laws. Oracle Advanced Security provides data encryption and strong authentication services to the Oracle database, safeguarding sensitive data against unauthorized access from the network and the operating system. It also protects against theft, loss, and improper decommissioning of storage media and database backups.

Reference: Oracle Advanced Security

http://www.oracle.com/technetwork/database/options/advanced-security/ds-security- advanced-security-11gr2-1-129479.pdf

Question No: 35

Which unique method of improving performance is NOT used by the Oracle Exadata Database Machine?

  1. Flash to improve query performance

  2. Reduces the amount of data required to flow through I/O

  3. Increases the I/O using InfiniBand

  4. Performs analysis in a special in-memory database

Answer: D

Reference: White paper, Exadata Smart Flash Cache and the Sun Oracle Database Machine

Question No: 36

You can perform what-if analysis of potential changes with Oracle Warehouse Builder.

  1. TRUE

  2. FALSE

Answer: A

Explanation: The Metadata Dependency Manager (MDM) enables you to plan your project by

previewing the impact of the changes or future changes for quot;what-ifquot; analysis. When you plan to introduce changes to your source systems, you can gauge the impact of that change on your warehouse design. If changes have already been introduced, then you can plan the time required to update your ETL design and rebuild your data warehouse.

Reference: Oracle庐 Warehouse Builder, Concepts, 11g Release 2 (11.2)

Question No: 37

Indentify the dimension that appears most often in queries in a data warehouse.

  1. Product dimension

  2. Time dimension

  3. Cost dimension

  4. Location dimension

Answer: B

Explanation: In a data warehouse, a dimension is a data element that categorizes each item in a data set into non-overlapping regions. A data warehouse dimension provides the means to quot;slice and dicequot; data in a data warehouse. Dimensions provide structured labeling information to otherwise unordered numeric measures. For example, quot;Customerquot;, quot;Datequot;, and quot;Productquot; are all dimensions that could be applied meaningfully to a sales receipt. A dimensional data element is similar to a categorical variable in statistics.

The primary function of dimensions is threefold: to provide filtering, grouping and labeling. For example, in a data warehouse where each person is categorized as having a gender of male, female or unknown, a user of the data warehouse would then be able to filter or categorize each presentation or report by either filtering based on the gender dimension or displaying results broken out by the gender.

Question No: 38

Which questions CANNOT be addressed by Oracle Data Mining?

  1. Fraud detection

  2. Prediction of customer behavior

  3. Root cause de

  4. Identify factors associated with a business problem

Answer: C

Explanation: Data Mining can provide valuable results:

*Predict customer behavior (Classification) (not B)

*Predict or estimate a value (Regression)

*Segment a population (Clustering)

*Identify factors more associated with a business problem (Attribute Importance) (not D)

  • Find profiles of targeted people or items (Decision Trees)

  • Determine important relationships and market baskets within the population (Associations)

  • Find fraudulent or rare events (Anomaly Detection) (not A)

Reference: Anomaly and Fraud Detection with Oracle Data Mining 11g Release 2

Question No: 39

Which is NOT an available composite partition in Oracle Database 11g?

  1. range-list

  2. list-list

  3. list-range

  4. interval-hash

Answer: D

Explanation: Extended Composite Partitioning

In previous releases of Oracle, composite partitioning was limited to Range-Hash and Range-List partitioning. Oracle 11g Release 1 extends this to allow the following composite partitioning schemes:

Range-Hash (available since 8i) Range-List (available since 9i) Range-Range

List-Range List-Hash List-List

Note: inverval-hash is a valid Interval partitioning. Reference:

http://www.oracle-base.com/articles/11g/PartitioningEnhancements_11gR1.php

Question No: 40

You are looking to create a RAC cluster to deliver high performance for your client#39;s data warehouse. Which statement is true about a configuration with a few large nodes versus a configuration with many smaller nodes?

  1. A few large nodes always perform better than many small nodes.

  2. A few large nodes always perform worse than many small nodes.

  3. It depends on the workload specifics and the effect of a node failure.

  4. Performance should be the same with either option.

Answer: D

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