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NEW QUESTION: 1
A German company wants to enter into a binding contract with a processor in the Netherlands for the processing at sensitive personal data of German data subjects. The Dutch Supervisory Authority is informed of the type of data and the aims of the processing, including the contract describing what data will be processed and what data protection procedures and practices will be in place.
According to the GDPH, what should the Dutch Supervisory Authority do in this scenario?
A. Supervise the processing of personal data in accordance with German Law.
B. Report the data processing to the German Supervisory Authority and leave the supervising to them.
C. The Dutch Supervisor Authority should check that adequate binding contracts are in place. The German Supervisory Authority should supervise.
D. Supervise the processing of personal data in accordance with Dutch Law.
Answer: C

NEW QUESTION: 2
Which of the following statements is not true?
A. A party outside the internal audit activity should oversee assurance engagements for functions over which the chief audit executive has responsibility.
B. The nature of consulting services that are performed by the internal audit activity should be defined in the audit charter.
C. The chief audit executive should decline a consulting engagement if the internal audit staff lacks the knowledge, skills, or other competencies needed to perform all or a part of the engagement.
D. It is inappropriate for internal auditors to provide consulting services relating to operations for which they had previous responsibilities.
Answer: D

NEW QUESTION: 3
会社はWindows Defender Advanced Threat Protection（ATP）を使用しています。 Windows Defender ATPには、次の表に示すマシングループが含まれています。

次の展示に示すように、computer1という名前のコンピューターをWindows Defender ATPにオンボードします。

ドロップダウンメニューを使用して、図に示されている情報に基づいて各ステートメントを完成させる回答の選択肢を選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

NEW QUESTION: 4
=======================================================================
Case Study: 3 Data Architect
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.
=======================================================================
You need to select the appropriate storage settings for the cube. Which settings should you choose?
Case Study Title (Case Study):
A. Hybrid OLAP (HOLAP) with proactive caching disabled
B. Multidimensional OLAP (MOLAP) with proactive caching disabled
C. Multidimensional OLAP (MOLAP) with proactive caching enabled and a rebuild interval of 24 hours
D. Relational OLAP (ROLAP) with proactive caching disabled
Answer: A

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