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NEW QUESTION: 1
プロジェクト管理！プロジェクト終了プロセスに備えて作業パフォーマンスデータを確認しています。データから、成果物の1つが受け入れられなかったことがわかります。成果物の受け入れを完了するために必要な推定作業により、プロジェクトの完了が2か月以上遅れます。
プロジェクトマネージャーは次に何をすべきですか？
A. スケジュールを更新して作業を実行します
B. リスクレジスタのウォッチリストを更新する
C. 予備費を割り当てて、完了に必要なリソースを調達します
D. 変更管理委員会（CCB）によるレビューの変更要求を発行します。
Answer: C

NEW QUESTION: 2
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
* Serve as a repository (or high volumes of large files in various formats.
* Implement optimized storage for big data analytics workloads.
* Ensure that data can be organized using a hierarchical structure.
Batch processing:
* Use a managed solution for in-memory computation processing.
* Natively support Scala, Python, and R programming languages.
* Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is

NEW QUESTION: 3
You are managing employee records. Due to reorganization, several employees from the Community Relations department in the location Atlanta are being assigned to a new division at the beginning of next year.
You have already created the future dated records in the job information portlet for those employees, including User A, as shown below.
User A is to be transferred from the location Atlanta to Charlotte on November 1, 2019. You insert a new Job Information record for User A with the Take Action command and change only the location to Charlotte. What are the new values for the Location and Division fields of the January 1, 2020 record? Note: There are 2 correct answers to this question.

A. Division: Healthcare
B. Division: Community Development
C. Location: Atlanta
D. Location: Charlotte
Answer: A,D