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NEW QUESTION: 1
Upon starting your database, you receive the following error:
SQL> startup
ORACLE instance started.
Total System Global Area 171581440 bytes
Fixed Size 1298640 bytes
Variable Size 146804528 bytes
Database Buffers 20971520 bytes
Redo Buffers 2506752 bytes
Database mounted.
ORA-00313: open failed for members of log group 1 of thread 1
ORA-00312: online log 1 thread 1: '/oracle01/oradata/orcl/redo01.log'
ORA-00312: online log 1 thread 1: '/oracle01/oradata/orcl/redo01a.log'
You can choose from the following steps:
a: Restore the database datafiles.
b: Issue the alter database clear unarchived logfile group 1 command.
c: Issue the alter database open command.
d: Issue the alter database open resetlogs command.
e: Recover the database using point-in-time recovery.
f: Issue the Startup Mount command to mount the database.
g: Back up the database.
Which is the correct order of these steps in this case?
A. f, b, c, g
B. a, f, e, d, g
C. a, f, c
D. f, e, d
E. The database cannot be recovered.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
1. one step of process must be ALTER DATABASE OPEN, since the database instance is started and mounted from clean shutdown.
2. After redo log clear done, you must backup the database immediately, so that you have a backup you can use for complete recovery without relying on the cleared log group.

NEW QUESTION: 2
You develop a SQL Server Integration Services (SSIS) package that imports Windows Azure SQL Database data into a data warehouse every night.
The Windows Azure SQL Database data contains many misspellings and variations of abbreviations. To import the data, a developer used the Fuzzy Lookup transformation to choose the closest-matching string from a reference table of allowed values. The number of rows in the reference table is very large.
If no acceptable match is found, the Fuzzy Lookup transformation passes a null value.
The current setting for the Fuzzy Lookup similarity threshold is 0.50.
Many values are incorrectly matched.
You need to ensure that more accurate matches are made by the Fuzzy Lookup transformation without degrading performance.
What should you do?
A. Increase the maximum number of matches per lookup.
B. Decrease the maximum number of matches per lookup.
C. Change the similarity threshold to 0.85.
D. Change the similarity threshold to 0.40.
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Similarity threshold
Set the similarity threshold at the component level by using the slider. The closer the value is to 1, the closer the resemblance of the lookup value to the source value must be to qualify as a match. Increasing the threshold can improve the speed of matching since fewer candidate records need to be considered.

NEW QUESTION: 3
Welche Stammdaten werden von SAP Master Data Governance, Financials (MDG F) unterstützt? Hinweis: Auf diese Frage gibt es 3 richtige Antworten.
A. Finanzplanungsdaten
B. Anlagenstamm
C. Profit-Center-Hierarchien
D. Hauptbuchkonten
E. Daten zur Finanzkonsolidierung
Answer: C,D,E

NEW QUESTION: 4
You need to design the recovery strategy for SSRS01.
What should the strategy include? (Each correct answer presents part of the solution. Choose all that apply.)
A. Restore the ReportServer and ReportServerTempDB databases with no recovery.
B. Restore the ReportServer and ReportServerTempDB databases with recovery.
C. Restore the database encryption key.
D. Restore the msdb database.
E. Restore the Report Server encryption key.
F. Re-create the SQL Server Agent jobs that are used to trigger schedules.
Answer: B,E,F
Explanation:
Explanation/Reference:
Testlet 1
General Background
You are a Data Architect for a company that uses SQL Server 2012 Enterprise edition.
You have been tasked with designing a data warehouse that uses the company's financial database as the data source. From the data warehouse, you will develop a cube to simplify the creation of accurate financial reports and related data analysis.
Background
You will utilize the following three servers:
ServerA runs SQL Server Database Engine. ServerA is a production server and also hosts the financial

database.
ServerB runs SQL Server Database Engine, SQL Server Analysis Services (SSAS) in multidimensional

mode, SQL Server Integration Services (SSIS), and SQL Server Reporting Services (SSRS).
ServerC runs SSAS in multidimensional mode.

The financial database is used by a third-party application and the table structures cannot be modified.

The relevant tables in the financial database are shown in the exhibit. (Click the Exhibit button.)

The SalesTransactions table is 500 GB and is anticipated to grow to 2 TB. The table is partitioned by month. It contains only the last five years of financial data. The CouponUsed, OnSale, and Closeout columns contain only the values Yes or No. Each of the other tables is less than 10 MB and has only one partition.
The SecurityFilter table specifies the sites to which each user has access.
Business Requirements
The extract, transform, load (ETL) process that updates the data warehouse must run daily between 8:00
P.M. and 5:00 A.M. so that it doesn't impact the performance of ServerA during business hours. The cube data must be available by 8:00 A.M.
The cube must meet the following business requirements:
Ensure that reports display the most current information available.

Allow fast access to support ad-hoc reports and data analysis.

Business Analysts will access the data warehouse tables directly, and will access the cube by using SSRS, Microsoft Excel, and Microsoft SharePoint Server 2010 PerformancePoint Services. These tools will access only the cube and not the data warehouse.
Technical Requirements
SSIS solutions must be deployed by using the project deployment model.
You must develop the data warehouse and store the cube on ServerB. When the number of concurrent SSAS users on ServerB reaches a specific number, you must scale out SSAS to ServerC and meet following requirements:
Maintain copies of the cube on ServerB and ServerC.

Ensure that the cube is always available on both servers.

Minimize query response time.

The cube must meet the following technical requirements:
The cube must be processed by using an SSIS package.

The cube must contain the prior day's data up to 8:00 P.M. but does not need to contain same-day

data.
The cube must include aggregation designs when it is initially deployed.

A product dimension must be added to the cube. It will contain a hierarchy comprised of product name

and product color.
Because of the large size of the SalesTransactions table, the cube must store only aggregations-- the data warehouse must store the detailed data. Both the data warehouse and the cube must minimize disk space usage.
As the cube size increases, you must plan to scale out to additional servers to minimize processing time.
The data warehouse must use a star schema design. The table design must be as denormalized as possible. The history of changes to the Customer table must be tracked in the data warehouse. The cube must use the data warehouse as its only data source.
Security settings on the data warehouse and the cube must ensure that queries against the SalesTransactions table return only records from the sites to which the current user has access.
The ETL process must consist of multiple SSIS packages developed in a single project by using the least amount of effort. The SSIS packages must use a database connection string that is set at execution time to connect to the financial database. All data in the data warehouse must be loaded by the SSIS packages.
You must create a Package Activity report that meets the following requirements:
Track SSIS package execution data (including package name, status, start time, end time, duration,

and rows processed).
Use the least amount of development effort.