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Eコマースサイトでは、戻ってきたユーザーがログインしてカスタマイズされたWebページを表示することができます。 ワークフローは以下の図のようになります。

アプリケーションがEC2インスタンスで実行されています。 Amazon RDSは、ユーザーアカウントと設定を保存するデータベースに使用されます。 ログインステップが完了するのを待っている間、Webサイトがフリーズするかロードが遅くなります。 サイトの残りのコンポーネントは最適化されています。
次のどの技術がこの問題を解決するでしょうか? (2つ選択してください。)
A. Amazon Application Load Balancerを使用してWebサイトへのトラフィックの負荷を分散します。
B. 非同期のLambda関数としてユーザログインページを実装してください。
C. データベースへの単一の読み取り要求として、何百人ものユーザーからのログイン要求をまとめてバッチ処理します。
D. MemCached用のAmazon ElastiCacheを使用してユーザーデータをキャッシュします。
E. コードを実行し続けることができるようにデータベースを非同期に呼び出します。
Answer: D,E

During an implementation, the Buyers will like to access the OTBI reports that are available in the Cloud Purchasing application. Identify the way to provide them easy access to Purchasing related OTBI reports?
A. Ask the buyer to run Scheduled Process to run the OTBI reports for Purchasing
B. Train the buyers to navigate to 'Functional Setup Manager' to access the reports
C. Enable the OTBI reports in Purchasing work area
D. Train the users to navigate to Business Intelligence applications to access the reports
Answer: C

You need to implement the date dimension in the Operations database.
What should you do?
A. Create three database dimensions. Add each database dimension as a cube dimension by setting the Referenced relationship type.
B. Create three database dimensions. Add each database dimension as a cube dimension by setting the Regular relationship type.
C. Create one database dimension. Add three cube dimensions based on the database dimension. Set the Regular relationship type for each cube dimension.
D. Create one database dimension. Add three cube dimensions based on the database dimension. Set the Referenced relationship type for each cube dimension.
Answer: C
Topic 5, Contoso, Ltd Case B
General Background
You are the business intelligence (BI) solutions architect for Contoso, Ltd, an online retailer.
You produce solutions by using SQL Server 2012 Business Intelligence edition and Microsoft SharePoint Server 2010 Service Pack 1 (SP1) Enterprise edition.
A SharePoint farm has been installed and configured for intranet access only. An Internet-facing web server hosts the company's public e-commerce website. Anonymous access is not configured on the Internet-facing web server.
Data Warehouse
The data warehouse is deployed on a 5QL Server 2012 relational database instance. The data warehouse is structured as shown in the following diagram.

The following Transact-SQL (T-SQL) script is used to create the FactSales and FactPopulation tables:

The FactPopulation table is loaded each year with data from a Windows Azure Marketplace commercial dataset. The table contains a snapshot of the population values for all countries of the world for each year. The world population for the last year loaded exceeds
6.8 billion people.
ETL Process
SQL Server Integration Services (SSIS) is used to load data into the data warehouse. All SSIS projects are developed by using the project deployment model.
A package named StageFactSales loads data into a data warehouse staging table. The package sources its data from numerous CSV files exported from a mainframe system. The CSV file names begin with the letters GLSD followed by a unique numeric identifier that never exceeds six digits. The data content of each CSV file is identically formatted.
A package named LoadFactFreightCosts sources data from a Windows Azure SQL Database database that has data integrity problems. The package may retrieve duplicate rows from the database.
The package variables of all packages have the RaiseChangedEvent property set to true.
A package-level event handler for the OnVariableValueChanged event consists of an Execute SQL task that logs the System::VariableName and System::VariableValue variables.
Data Models
SQL Server Analysis Services (SSAS) is used to host the Corporate BI multidimensional database. The Corporate BI database contains a single data source view named Data Warehouse. The Data Warehouse data source view consists of all data warehouse tables. All data source view tables have been converted to named queries.
The Corporate BI database contains a single cube named Sales Analysis and three database dimensions: Date, Customer and Product. The dimension usage for the Sales Analysis cube is as shown in the following image.

The Customer dimension contains a single multi-level hierarchy named Geography. The structure of the Geography hierarchy is shown in the following image.

The Sales Analysis cube's calculation script defines one calculated measure named Sales Per Capita. The calculated measure expression divides the Revenue measure by the Population measure and multiplies the result by 1,000. This calculation represents revenue per 1,000 people.
The Sales Analysis cube produces correct Sales Per Capita results for each country of the world; however, the Grand Total for all countries is incorrect, as shown in the following image (rows 2-239 have been hidden).

A role named Analysts grants Read permission for the Sales Analysis cube to all sales and marketing analysts in the company.
SQL Server Reporting Services (SSRS) is configured in SharePoint integrated mode. All reports are based on shared data sources.
Corporate logo images used in reports were originally configured as data-bound images sourced from a SQL Server relational database table. The image data has been exported to JPG files. The image files are hosted on the Internet-facing web server. All reports have been modified to reference the corporate logo images by using the fully qualified URLs of the image files. A red X currently appears in place of the corporate logo in reports.
Users configure data alerts on certain reports. Users can view a report named Sales Profitability on demand; however, notification email messages are no longer being sent when Sales Profitability report data satisfies alert definition rules. The alert schedule settings for the Sales Profitability report are configured as shown in the following image.

Business Requirements
Data Models
Users must be able to: - Provide context to measures and filter measures by using all related data warehouse dimensions. - Analyze measures by order date or ship date.
Additionally, users must be able to add a measure named Sales to the report canvas by clicking only once in the Power View field list. The Sales measure must allow users to analyze the sum of the values in the Revenue column of the FactSales data warehouse table. Users must be able to change the aggregation function of the Sales measure.
Analysis and Reporting
A sales manager has requested the following query results from the Sales Analysis cube
for the 2012 fiscal year:
- Australian postal codes and sales in descending order of sales.
- Australian states and the ratio of sales achieved by the 10 highest customer sales
made for each city in that state.
Technical Requirements ETL Processes
If an SSIS package variable value changes, the package must log the variable name and the new variable value to a custom log table.
The StageFactSales package must load the contents of all files that match the file name pattern. The source file name must also be stored in a column of the data warehouse staging table. In the design of the LoadFactSales package, if a lookup of the dimension surrogate key value for the product code fails, the row details must be emailed to the data steward and written as an error message to the SSIS catalog log by using the public API.
You must configure the LoadFactFreightCosts package to remove duplicate rows, by using the least development effort.
Data Models
Users of the Sales Analysis cube frequently filter on the current month's data. You must ensure that queries to the Sales Analysis cube default to the current month in the Order Date dimension for all users.
You must develop and deploy a tabular project for the exclusive use as a Power View reporting data source. The model must be based on the data warehouse. Model table names must exclude the Dim or Fact prefixes. All measures in the model must format values to display zero decimal places.
Analysis and Reporting
Reports must be developed that combine the SSIS catalog log messages with the package variable value changes.

Der Projektmanager erhält zwei Teams, die nur fünf Tage pro Woche arbeiten dürfen. Die ersten Berechnungen geben einen Projektzeitplan von zwei Wochen an. Eines der Teams wird jedoch aufgrund einer vorherigen Verpflichtung in Woche 1 nur zweieinhalb Tage verfügbar sein. Die Zeitleiste wird auf drei Wochen überarbeitet.
Mit welcher Optimierungstechnik wurde die Zeitleiste überarbeitet?
A. Kritisches Kettenmanagement
B. Verwaltung kritischer Pfade
C. Ressourcenglättung
D. Ressourcenebenen
Answer: D

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